{
    "paper_id": "O00-1011",
    "header": {
        "generated_with": "S2ORC 1.0.0",
        "date_generated": "2023-01-19T07:59:12.678572Z"
    },
    "title": "",
    "authors": [],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "",
    "pdf_parse": {
        "paper_id": "O00-1011",
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        "body_text": [
            {
                "text": "\u5047\u8a2d\u6709\u4e00\u5305\u542b M \u500b \u7684 \u9663\u5217\uff0c\u6bcf\u4e00\u7d44\u76f8\u9130\u7684 \u7684\u8ddd \u70ba d\uff0c \u6709\u4e00\u8a9e\u97f3 \u8a0a (\u5047\u8a2d\u70ba\u5e73\u9762\u6ce2)\u5f9e\u6211\u5011 \u51fa\u7684\u6700\u4f73\u65b9\u5411 s \u50b3 \u904e\u4f86\uff0c \u7684\u8f38\u51fa\u70ba i t x \uff0c M i 1 \uff0c \u5247\u5728\u6642\u9593 t \u7684\u6642\u5019\uff0c\u7576\u7b2c i \u5230\u5e73\u9762\u6ce2\u7684\u8a0a \uff0c\u7b2c i+1 \u5247\u9700\u7b49\u5230 \u6ce2\u518d\u524d\u9032 \u8ddd R ( s d R cos = )\u65b9\u53ef \u5230\u8a0a \uff0c\u5982\u5716\u4e8c\u6240\u793a\u3002 \u82e5 \u6ce2\u7684\u901f\u5ea6\u70ba C\uff0c\u5247\u7b2c i+1 \u500b \u7684\u6642\u9593 C d C R s cos = = (1) 1 + + = i t i t x x \uff0c\u56e0\u6b64\u6211\u5011\u53ef\u4ee5\u4f30\u7b97\u7b2c i \u500b \u8207\u7b2c 1 \u500b \u7684\u95dc\u4fc2\u5982\u4e0b\uff1a 1 ) 1 ( \u2212 + = i t i t x x (2)",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Delay-and-Sum Beamformer",
                "sec_num": "2.1"
            },
            {
                "text": "\u800c\u6574\u500b Delay-and-Sum Beamformer \u7684\u8f38\u51fa t",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Delay-and-Sum Beamformer",
                "sec_num": "2.1"
            },
            {
                "text": "x \uff0c\u5982\u5716\u4e09\u6240\u793a\uff0c\u5c31\u662f\u5c07\u6bcf\u500b \u9593\u7684\u6642\u9593",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Delay-and-Sum Beamformer",
                "sec_num": "2.1"
            },
            {
                "text": "\u4f5c\u88dc \u5f8c\u5408\u6210\u518d\u53d6\u5e73\u5747\u800c\u5f97 \u2211 = \u2212 + = M i i i t t M 1 ) 1 ( 1 x x (3)",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Delay-and-Sum Beamformer",
                "sec_num": "2.1"
            },
            {
                "text": "\u5716\u4e8c\u3001\u76f8\u9130 \u7684\u6642\u9593 \u5716\u4e09\u3001Delay-and-Sum Beamformer \u6d41\u7a0b\u5716 ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Delay-and-Sum Beamformer",
                "sec_num": "2.1"
            },
            {
                "text": "EQUATION",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [
                    {
                        "start": 0,
                        "end": 8,
                        "text": "EQUATION",
                        "ref_id": "EQREF",
                        "raw_str": "\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5\u7684\u4e3b\u8981\u76ee\u7684\u5728\u65bc\u4f30 \u51fa\u8a9e\u8005\u767c \u7684\u65b9\u5411\uff0c\u5176\u7cfb\u7d71\u6d41\u7a0b\u5716\u5982\u5716\u56db\u6240\u793a\uff0c\u6211 \u5011\u5c07\u5206\u6210\u4e0b\u5217\u4e09\u90e8\u4efd\u505a\u8aaa\u660e\u3002 \u5716\u56db\u3001\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5(SLA)\u6d41\u7a0b\u5716 \u9996\u5148\uff0c\u6211\u5011\u5c07 M \u500b \u5728\u6642\u57df\u4e0a\u7684\u8a9e\u97f3\u8a0a M i i t ,..., 1 , = x \u7d93\u904e\u5feb\u901f \u5229\u8449\u8f49\u63db\u5f8c\u5f97\u5230 \u7684 \u5728\u983b\u7387\u4e0a\u7684\u8a0a 1 ,..., 0 , ,..., 1 ), ( \u2212 = = K k M i k i t X \uff0c\u5176\u4e2d i \u8868\u793a \u7684 \u6578\uff0ck \u8868\u793a \u983b\u7387\u7684 \u6578\uff0ct \u8868\u793a\u97f3 \u7684 \u6578\u3002 \u7b2c\u4e8c\u90e8\u5206\uff0c\u6211\u5011\u8a08\u7b97\u4e0d\u540c \u97f3\u65b9\u5411\u89d2\u5ea6 180 ,..., 1 = \u7684 \u9593\u529f\u7387\u983b \u2211 \u2212 = = 1 0 ) , ( ) ( K k t t k P P \uff0c 180 , , 1 L = (4) \u5176\u4e2d 2 1 } cos ) 1 ( 2 exp{ ) ( ) , ( \u2211 = \u2212 = M i k i t t c d i f j k k P \u03c0 X",
                        "eq_num": "(5)"
                    }
                ],
                "section": "\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5(Speaker Localization Algorithm, SLA)",
                "sec_num": "2.2"
            },
            {
                "text": "\u6642\u9593 \u3002\u5176\u57fa\u672c\u60f3\u6cd5\u662f\u5047\u8a2d\u7b2c i \u500b \u548c\u5176\u6240\u76f8\u9130\u7684\u7b2c i+1 \u500b \u5728\u7b2c L \u500b\u6578\u4f4d\u9ede\u5f8c \u7684\u8a9e\u97f3\u8a0a \u5206\u5225\u8868\u793a\u5982\u4e0b\uff1a i N L i L i L + + x x x ,..., , 1 \u548c 1 1 1 1",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5(Speaker Localization Algorithm, SLA)",
                "sec_num": "2.2"
            },
            {
                "text": ",..., , ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5(Speaker Localization Algorithm, SLA)",
                "sec_num": "2.2"
            },
            {
                "text": "EQUATION",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [
                    {
                        "start": 0,
                        "end": 8,
                        "text": "EQUATION",
                        "ref_id": "EQREF",
                        "raw_str": "+ + + + + + + + i N L i L i L x x x \u5176\u4e2d\u6211\u5011\u53d6\u51fa N \u500b\u6578\u4f4d\u9ede\uff0c\u5982\u5716\u4e94\u6240\u793a\u3002 \u5728\u4e0d\u8003\u616e \u97f3\u4ee5\u53ca\u8a0a \u6e1b\u7684\u60c5\u5f62\u4e0b\uff0c\u82e5 \u70ba i \u548c i+1 \u9593\u7684\u6642\u9593 \uff0c\u5247 i t x \u548c 1 + + i t x \u4e4b\u9593\u5177\u6709\u6700\u5927\u7684\u76f8\u95dc\u6027\u4e14 \u2211 + = + + N L L t i t i t 1 x x \u9ede \u548c\u70ba\u6700\u5927\uff0c\u6b64\u4e00 \u548c\u53ef\u7a31\u4e4b\u70ba Time Domain Cross Correlation\u3002 \u5716\u4e94\u3001TDCC\u793a\u610f\u5716 \u7d93\u7531\u4ee5\u4e0a\u7684\u60f3\u6cd5\u6211\u5011\u767c\u5c55\u51fa TDCC \u7684\u6f14\u7b97\u6cd5\uff1a\u82e5\u73fe\u6709\u4e00 \u9663\u5217\u5305\u542b\u6709 M \u500b \uff0c i \u65bc\u6642\u9593 t \u6240 \u5230\u7684\u8a0a \u7a31\u70ba i t x \uff0c\u5247\u5c0d\u8a9e\u97f3\u8a0a \u4e2d\u4efb\u4e00\u97f3 m \u7684 TDCC \u5b9a\u7fa9\u5982\u4e0b \u2211\u2211 = = + \u2212 + \u2212 = M i N j i j p m j p m m C 2 1 ) 1 ( 1 ) 1 ( ) ( x x",
                        "eq_num": "("
                    }
                ],
                "section": "\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5(Speaker Localization Algorithm, SLA)",
                "sec_num": "2.2"
            },
            {
                "text": "\u5176\u4e2d \u2211\u2211 = = \u2212 + + \u2212 + \u2212 = M i N j i i j p m j p m m C 2 1 ) 1 ( ) 1 ( 1 ) 1 ( ) , ( x x (9) \u9019\u88e1\u6211\u5011\u662f\u4ee5\u8a9e\u53e5\u4e2d\u80fd\u91cf\u6700\u9ad8\u7684\u97f3 \u70ba\u57fa\u6e96\u4f86\u8a08\u7b97\u6642\u9593 \uff0c\u53e6\u5916\u82e5\u5c07\u8a9e\u53e5 \u5168\u90e8\u97f3 \u7684 TDCC \u52a0\u8d77\u4f86\uff0c\u6839\u64da\u6b64 \u52a0\u503c\u5247\u76f8\u9130 \u9593\u7684\u6642\u9593 A \u02c6\u70ba \u2211 = m A ) C(m, max",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5(Speaker Localization Algorithm, SLA)",
                "sec_num": "2.2"
            },
            {
                "text": ") ( ) ( 2 / 1 2 / 1 2 / 1 ) 2 ( 1 ) , | ( s t s s t o o s n s s t e o P \u00b5 \u00b5 \u03c0 \u00b5 \u2212 \u03a3 \u2212 \u2212 \u2212 \u03a3 = \u03a3 (11) \u5176\u4e2d s \u00b5 \u8868\u793a\u5e73\u5747\u503c\u5411\u91cf\uff0c s \u03a3 \u8868\u793a\u8b8a\u7570\u6578\u77e9\u9663\uff0c t o \u70ba\u89c0 \u5230\u7684\u7279\u5fb5\u5411\u91cf\uff0cn \u70ba\u5411\u91cf\u7684 \u5ea6\u3002 \u5b9a\u7fa9\u4e00\u500b\u5927\u5c0f\u70ba ) 1 ( + \u00d7 n n \u7684\u8f49 \u77e9\u9663 s W \uff0c \u53ef\u5c07 \u5c55\u5f8c\u7684\u5e73\u5747\u503c\u5411\u91cf s \u8abf\u6574\u800c\u5f97\u5230\u65b0\u7684 \u5e73\u5747\u503c\u5411\u91cf s s s W \u00b5 = (12) \u5176\u4e2d = n s \u00b5 \u00b5 \u00b5 ,..., , , 2 1 \uff0c \u662f\u5728\u9032\u884c\u56de\u6b78\u8a08\u7b97\u6642\u8003\u616e\u662f\u5426\u4f7f\u7528 \u5dee\u91cf(\u4f7f\u7528\u5247 \u70ba 1\uff0c\u4e0d\u4f7f \u7528\u5247\u70ba 0)\u3002\u56e0\u6b64\u8abf\u6574\u904e\u5f8c\u7684\u9ad8\u65af\u6a5f\u7387\u5206\u4f48\u5982\u4e0b\u6240\u793a ) ( ) ( 2 / 1 2 / 1 2 / 1 ) 2 ( 1 ) , ,",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5(Speaker Localization Algorithm, SLA)",
                "sec_num": "2.2"
            }
        ],
        "back_matter": [],
        "bib_entries": {
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                    {
                        "first": "S",
                        "middle": [],
                        "last": "Nakamura",
                        "suffix": ""
                    },
                    {
                        "first": "K",
                        "middle": [],
                        "last": "Shikano",
                        "suffix": ""
                    }
                ],
                "year": 1998,
                "venue": "Proc. of ICSLP '98",
                "volume": "",
                "issue": "",
                "pages": "381--384",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "T. YAMADA, S. Nakamura and K. Shikano, \"An Effect of Adaptive Beamforming on 3-D Viterbi Search\", In Proc. of ICSLP '98, pages 381-384, December 1998b.",
                "links": null
            },
            "BIBREF11": {
                "ref_id": "b11",
                "title": "Simultaneous Recognition of Multiple Sound Sources Based on 3-D N-Best Search Using Microphone Array",
                "authors": [
                    {
                        "first": "T",
                        "middle": [],
                        "last": "Yamada",
                        "suffix": ""
                    },
                    {
                        "first": "S",
                        "middle": [],
                        "last": "Nakamura",
                        "suffix": ""
                    },
                    {
                        "first": "K",
                        "middle": [],
                        "last": "Shikano",
                        "suffix": ""
                    }
                ],
                "year": 1999,
                "venue": "Proc. of Eurospeech '99",
                "volume": "1",
                "issue": "",
                "pages": "69--72",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "T. YAMADA, S. Nakamura and K. Shikano, \"Simultaneous Recognition of Multiple Sound Sources Based on 3-D N-Best Search Using Microphone Array\". In Proc. of Eurospeech '99, Volume 1, Page 69-72, September 1999.",
                "links": null
            }
        },
        "ref_entries": {
            "TABREF0": {
                "content": "<table><tr><td colspan=\"4\">\u4e00\u822c\u7684\u8a9e\u97f3\u8fa8\u8a8d\u7686\u4f7f\u7528\u55ae\u4e00</td><td>\u505a\u70ba\u8a9e\u97f3\u8a0a \u7684\u8f38\u5165\uff0c\u5728</td><td>\u7684</td><td>\u4e0b\u5df2\u6709\u4e0d\u932f\u7684\u8fa8</td></tr><tr><td colspan=\"5\">\u8b58\u6210\u679c\uff0c\u7136\u800c\uff0c\u7576\u61c9\u7528\u5728 \u97f3\u5f88\u5927\u7684</td><td>\u88e1\uff0c\u8a9e\u97f3\u8fa8\u8b58\u7684\u6548\u679c\u5c07\u5927</td><td>\uff0c\u56e0\u6b64\uff0c\u5982\u4f55 \u5236</td></tr><tr><td colspan=\"4\">\u97f3\u4e26\u52a0 \u8a9e\u97f3\u8a0a \u5df2\u6210\u70ba</td><td>\u8a9e\u97f3\u8fa8\u8b58\u7684\u95dc \u6027\u6280\u8853\u3002\u56e0\u6b64\u672c\u8ad6\u6587\u4e2d\u6211\u5011\u4f7f\u7528\u4e00\u7d44\u9060\u8ddd</td></tr><tr><td colspan=\"5\">\u9663\u5217\u505a\u8a9e\u97f3\u8a0a \u8f38\u5165\uff0c\u7136\u5f8c\u4f7f\u7528 TDCC \u5c07\u6bcf\u500b</td><td>\u4e4b\u9593\u7684\u6642\u9593</td><td>\u8a08\u7b97\u51fa\u4f86\uff0c\u518d\u5229</td></tr><tr><td colspan=\"5\">\u5efa \u7528 Delay-and-Sum Beamformer \u7684\u65b9\u5f0f\uff0c\u5f97\u5230\u4e00\u7d44\u5177 \u7c21</td><td>\u6027\u4e14\u52a0 \u904e\u5f8c\u7684\u8a9e\u97f3\u8a0a \u3002\u70ba\u4e86\u4f7f\u52a0</td></tr><tr><td colspan=\"5\">\u570b\u7acb\u6210\u529f\u5927\u5b78\u8cc7\u8a0a\u5de5\u7a0b\u5b78\u7cfb \u904e\u7684\u8a9e\u97f3\u8a0a \u5728\u9032\u884c\u96b1\u85cf\u5f0f\u99ac\u53ef\u592b\u6a21\u578b(Hidden Markov Model, HMM)\u70ba\u4e3b\u8a9e\u97f3\u8fa8\u8b58\u6642\u6709\u66f4</td></tr><tr><td colspan=\"5\">Email\uff1ajtchien@mail.ncku.edu.tw \u4f73\u7684\u8fa8\u8b58\u6548\u679c\uff0c\u6211\u5011\u4f7f\u7528\u6700\u4f73\u76f8 \u5ea6\u7dda\u6027\u56de\u6b78\u7406\u8ad6(maximum likelihood linear regression,</td></tr><tr><td colspan=\"5\">MLLR) (Leggetter and Woodland, 1995)\u5c07\u539f \u8a9e\u97f3\u8a13\u7df4\u51fa\u4f86\u7684\u96b1\u85cf\u5f0f\u99ac\u53ef\u592b\u6a21\u578b\u53c3\u6578\u505a\u8abf</td></tr><tr><td>\u6574\uff0c\u4ee5\u88dc</td><td colspan=\"4\">\u6458\u8981 \u8a9e\u97f3\u8207\u6a21\u578b\u53c3\u6578\u4e4b\u9593\u7684\u4e0d \u914d\u3002</td></tr><tr><td colspan=\"5\">\u672c\u7bc7\u8ad6\u6587\u63d0\u51fa\u4e00\u7a2e\u53ef\u61c9\u7528\u65bc \u97f3 \u76ee\u524d \u7684\u5b78\u8853\u7814\u7a76\u6a5f\u69cb\u5c0d\u65bc\u67b6\u69cb\u65bc</td><td>\u4e0b</td><td>\u9663\u5217(Microphone Array)\u7684\u8a9e\u97f3\u8fa8\u8b58\u6f14\u7b97 \u9663\u5217\u4e0a\u7684\u8a9e\u97f3\u8655\u7406\u6280\u8853\u5c1a\u5c6c\u8d77\u6b65\u968e\u6bb5\uff0c\u5728\u4e2d</td></tr><tr><td colspan=\"5\">\u6cd5\uff0c\u5176\u4e3b\u8981\u7684\u76ee\u7684\u5728\u65bc \u6587\u8a9e\u97f3\u8fa8\u8b58\u4e0a\u7684\u61c9\u7528\u767c\u8868\u5728\u76f8\u95dc\u5b78\u8853\u6703 \u53ca \u50b3\u7d71\u96fb \u8a9e\u97f3\u8fa8\u8b58\u7cfb\u7d71\u9700\u8981\u4f7f\u7528\u8005\u982d \u6216 \u8ad6\u6587\u5c1a\u4e0d\u591a\u898b\uff0c\u7136\u800c\uff0c\u570b\u5916\u7684\u7814\u7a76\u6a5f\u69cb\u5247 \u7684\u4e0d\u65b9 \u3002</td></tr><tr><td colspan=\"5\">\u70ba\u4e86 \u9664\u9060\u8ddd \u5df2 \u5165\u6b64\u4e00 \u57df\uff0c\u4e26\u4e14\u7372\u5f97\u4e0d\u932f\u7684\u6210\u679c\uff0c\u6bd4\u8f03\u6709\u540d\u7684\u5305\u62ec\u4e09\u5927\u985e\u7684\u65b9\u6cd5\uff0c\u7b2c\u4e00\u985e\u662f\u8457\u91cd\u5728\u4e0d \u7684 \u97f3 \uff0c\u6211\u5011\u7684\u65b9\u6cd5\u662f\u5148\u5c07\u6bcf\u500b \u96c6\u5230\u7684\u8a9e\u97f3\uff0c\u5229\u7528\u8a9e\u97f3</td></tr><tr><td>\u5230 \u6bcf\u500b \u540c</td><td colspan=\"4\">\u89d2\u5ea6\u7684\u4e0d\u540c\uff0c\u4f7f\u7528 Time Domain Cross Correlation (TDCC)\u6f14\u7b97\u6cd5 \u51fa\u8a9e\u8005\u767c \u9593\u6642\u9593 \u7684\u8a08\u7b97\uff0c \u4e3b\u8981\u662f\u5229\u7528\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5\u4f86\u8a08\u7b97\u4e0d\u540c \u9593\u7684\u6642\u9593</td></tr><tr><td colspan=\"5\">\u97f3\u7684\u65b9\u5411\u53ca\u8a9e\u97f3\u5230 \u6bcf\u500b \u53ef \u7684\u6642\u9593</td><td>\uff0c\u518d\u61c9\u7528 Delay-and-Sum Beamformer \u9663\u5217\u8a0a \u8655</td></tr><tr><td colspan=\"5\">\u7406\u6280\u8853\u5c07\u8a9e\u97f3\u8a0a \u52a0 \uff0c\u6700\u5f8c\u6211\u5011\u518d\u5c07\u52a0 \u904e\u7684\u8a9e\u97f3\u8a0a \u548c\u8a9e\u97f3\u6a21\u578b\u53c3\u6578\u9593\u7684\u4e0d \u914d\u7528\u6700\u4f73</td></tr><tr><td colspan=\"5\">\u76f8 \u5ea6\u7dda\u6027\u56de\u6b78(MLLR)\u7684\u6a21\u578b\u8abf\u6574\u6f14\u7b97\u6cd5\u4f86 \u9593\u6642\u9593 \u4f75\u5165\u96b1\u85cf\u5f0f\u99ac\u53ef\u592b\u6a21\u578b\u7684\u53c3\u6578\uff0c \u7684\u89c0 \u662f \u3002\u5728 \u97f3</td><td>\u4e0b\u4f7f\u7528 \u50b3\u7d71\u8a9e\u97f3\u96b1\u85cf\u5f0f\u99ac\u53ef\u592b\u6a21\u578b\u7684\u53c3 \u9663\u5217\u4e4b\u9023\u7e8c\u6578\u5b57</td></tr><tr><td colspan=\"5\">\u8fa8\u8b58\u5be6\u9a57\u4e2d\uff0c\u6211\u5011\u63d0\u51fa\u4f86\u7684\u65b9\u6cd5\u5c0d\u65bc\u63d0\u5347\u8fa8\u8b58\u7387\u6709 \u597d\u7684\u6548\u679c\u3002 \u6578\uff0c\u52a0\u5165\u5404\u7a2e\u4e0d\u540c\u7684\u8a9e\u8005\u89d2\u5ea6\uff0c\u4e26\u4f7f\u7528\u4e00\u7a2e\u4e09 \u7684 \u7279\u6bd4\u6f14\u7b97\u6cd5(Three-Dimensional Viterbi</td></tr><tr><td colspan=\"2\">Search)\u4f5c\u8a9e\u97f3\u8fa8\u8b58</td><td/><td/></tr><tr><td colspan=\"2\">1. \u5c0e\u8ad6</td><td/><td/></tr><tr><td colspan=\"2\">\u73fe\u5be6\u751f</td><td>\u4e2d\uff0c</td><td colspan=\"2\">\u4e86\u5404\u5f0f\u5404\u6a23\u7684 \u97f3\u548c\u56de\u97f3\uff0c\u9019\u4e9b</td><td>\u6703 \u91cd\u7684 \u4f4e\u8a9e\u97f3\u8fa8\u8a8d\u7cfb\u7d71</td></tr><tr><td colspan=\"5\">\u7684\u6548\u80fd\uff0c\u5176\u4e2d\u4e4b\u4e00\u7684\u89e3\u6c7a\u65b9\u5f0f\u662f\u4f7f\u7528\u982d \u5f0f</td><td>(Head-Mounted Microphone)\uff0c\u4f7f\u5f97 \u97f3</td></tr><tr><td>\u548c</td><td colspan=\"3\">\u76e1\u53ef\u80fd\u7684 \u8fd1\uff0c\u4f86 \u4f4e</td><td>\u97f3\u548c\u56de\u97f3\u7684\u5f71\u97ff\u3002\u7136\u800c\u4f7f\u7528\u982d \u5f0f</td><td>\u8a2d \u6703\u9020\u6210</td></tr><tr><td colspan=\"5\">\u4f7f\u7528\u8005\u7684\u4e0d \uff0c\u56e0\u6b64\u5982\u4f55\u767c\u5c55\u4ee5\u514d \u5f0f</td><td>(Hands-Free Microphone)\u70ba\u4e3b\u7684\u8a9e\u97f3\u8fa8\u8a8d\u7cfb\u7d71\u5df2</td></tr><tr><td colspan=\"4\">\u6210\u70ba\u4e00\u500b\u76f8\u7576\u91cd\u8981\u7684\u7814\u7a76 \u984c\u3002</td></tr><tr><td colspan=\"2\">\u57fa\u672c\u4e0a\uff0c\u4f7f\u7528</td><td colspan=\"3\">\u9663\u5217\u53ef\u4ee5\u9032\u884c\u9060\u8ddd</td><td>\u97f3\uff0c\u56e0\u6b64\u53ef\u4ee5\u89e3\u6c7a\u982d \u5f0f</td><td>\u9020\u6210\u4f7f\u7528\u8005</td></tr><tr><td colspan=\"3\">\u4e0d \u7684\u554f\u984c\uff0c\u800c\u6211\u5011\u5e38\u7528\u7684</td><td/><td>\u9663\u5217\u8a0a \u8655\u7406\u6280\u8853\u662f \u7528 Delay-and-Sum Beamformer\uff0c</td></tr><tr><td>\u53ef\u4ee5</td><td colspan=\"4\">\u97f3\u548c\u56de\u97f3\u5c0d\u8a9e\u97f3\u8a0a \u7684\u5f71\u97ff\uff0c\u9084\u539f\u51fa</td><td>\u7684\u8a9e\u97f3\u3002\u800c\u4e14\u6b64\u4e00\u6280\u8853\u4e26\u975e\u91dd\u5c0d\u7279</td></tr><tr><td>\u5b9a \u97f3</td><td colspan=\"4\">\uff0c \u53ef\u9069\u7528\u65bc\u4efb\u4f55 \u97f3</td><td>\u4e0b\uff0c\u5f97\u5230 \u4eba \u610f\u7684\u6548\u679c\u3002\u5728\u672c\u8ad6\u6587\u4e2d\uff0c\u6211\u5011\u5c07</td></tr><tr><td colspan=\"2\">\u9663\u5217\u61c9\u7528\u65bc \u4f4e</td><td/><td colspan=\"2\">\u97f3\u7684</td><td>\uff0c\u4ee5 \u5230\u63d0\u9ad8\u8a9e\u97f3\u8fa8\u8a8d\u7387\u4e4b\u76ee\u7684\u3002</td></tr></table>",
                "text": "",
                "num": null,
                "html": null,
                "type_str": "table"
            },
            "TABREF6": {
                "content": "<table><tr><td>\u591a\u901a \u97f3 SigC31-4 \u63a5\u982d\u7d93\u7531\u5de5\u4f5c\u96fb\u8def\u548c \u76f8\u9023\u63a5\uff0c\u900f\u904e\u6240\u9644\u7684 \u9ad4\u5373\u53ef\u5229\u7528 4 \u500b \u6211\u5011\u4f7f\u7528\u570b \u97f3 \u516c \u6240\u751f\u7522\u7684\u5168\u65b9\u5411\u96fb\u5bb9\u5f0f (Omni-directional Condenser \u540c\u6642 \u97f3\uff0c\u96fb\u5bb9\u5f0f Microphone)\uff0c\u578b \u70ba ECM9D\uff0c\u6240\u5c0d\u61c9\u7684\u983b \u70ba 20~10000Hz\uff0c \u5ea6\u70ba-38 3dB\uff0c\u8a0a \u6bd4 (signal-to-noise ratio, SNR)\u5927\u65bc 60dB\uff0c\u5de5\u4f5c\u96fb\u58d3\u5247\u4ecb\u65bc DC 3V \u81f3 DC 10V \u4e4b\u9593\u3002\u5de5\u4f5c\u96fb\u8def\u4e3b \u524d\u5f8c\u7684 \u97f3\u548c\u6578\u5b57\u9593\u7684 \u97f3\uff0c\u6240\u4ee5\u7e3d\u5171\u7684 \u6578\u76ee\u70ba 73 \u500b\u3002\u6bcf\u4e00\u500b \u5305\u542b 4 \u500b \u5408\u6578\uff0c \u56e0\u6b64\u5171\u6709 292 \u500b \u5408\u6578\u3002 \u8a9e\u6599\u662f\u5728\u5be6\u9a57 \u4e2d\u4f7f\u7528\u9060\u8ddd \u9663\u5217\u6240 \uff0c\u6211\u5011\u6a21 \u4e86\u4e09\u7a2e\u4e0d\u540c \u901f\u7684\u8def \u6cc1\uff0c\u5206\u5225\u70ba 0 km/h\u300150 km/h \u548c 90 km/h\u3002\u5728 0 km/h \u8def\u6cc1\u4e0b\u4e0d\u52a0\u4efb\u4f55 \u97f3\uff0c\u800c 50 km/h \u548c 90 km/h \u8def\u6cc1\u5247\u5229\u7528 \u653e\u51fa \u65bc\u6642\u901f 50 km/h \u548c 90 km/h \u6642\u6240 \u4e0b\u7684 \u97f3\u4f86\u6a21 \u3002 \u97f3\u6642\u8a9e\u8005\u8ddd \u4e2d\u5fc3 120 \u516c\u5206\u548c \u9663\u5217\u7684 \u89d2 \u70ba 60 \u5ea6\uff0c \u97f3 \u5247 \u653e\u65bc\u8ddd \u4e2d\u5fc3 80 \u516c\u5206\u8655\u548c \u7684\u7684 \u89d2 75 \u5ea6\uff0c \u9663\u5217\u662f\u7dda\u6027\u914d \u7684\uff0c\u76f8\u9130 \u7684\u9593\u8ddd\u70ba 10 \u516c Delay-and-Sum Beamformer \u8655\u7406\u5f8c\u7684\u8a9e\u97f3\u8a0a \u5206\u5225\u8a08\u7b97\u5176\u8fa8\u8a8d\u7d50\u679c\uff0c\u8fa8\u8a8d\u7d50\u679c\u5982\u8868\u4e8c\u6240\u793a\u3002 \u89c0\u5bdf\u5be6\u9a57\u7d50\u679c\u6211\u5011\u53ef\u4ee5\u767c\u73fe\u5728\u4e0d\u540c\u8def\u6cc1\u4e0b\u6700\u4f73\u8fa8\u8a8d\u7387\u90fd\u51fa\u73fe\u5728 60 \uff0c\u6b64\u4e00\u7d50\u679c\u548c\u6211\u5011\u5be6 \u4e0a \u8a9e\u97f3\u6642\u7684\u65b9\u5411\u662f\u5341\u5206 \u5408\u7684\u3002 Digit Error Rate (%) \u8def\u6cc1 0 km/h 50 km/h 90 km/h Mic 1 47.0 52.1 55.1 Mic 2 42.0 48.3 3.4 \u53d6\u6a23\u983b\u7387\u5c0dSLA\u548cTDCC\u7684\u5f71\u97ff \u7d93\u7531\u4ee5\u4e0a\u7684\u5be6\u9a57\u7d50\u679c\uff0c\u6211\u5011\u767c\u73fe\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5\u7684\u6548\u80fd\u8f03\u5dee\u3002 \u7814\u7a76\u5176\u539f\u56e0\u5f8c\u767c\u73fe\uff0c \u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5\u662f\u5148\u6c42\u51fa\u8a9e\u8005\u7684\u65b9\u5411 s \uff0c\u518d\u5229\u7528\u516c\u5f0f C d b s cos Rate) (Sampling Rate) Sampling ( = = 3.5 \u52a0\u5165\u8a9e\u97f3\u6a21\u578b\u8abf\u6574\u7684\u5be6\u9a57\u7d50\u679c \u63a5\u4e0b\u4f86\u7684\u5be6\u9a57\u8457\u91cd\u65bc \u89e3\u8a9e\u97f3\u6a21\u578b\u8abf\u6574\u5c0d \u9663\u5217\u8a9e\u97f3\u8fa8\u8a8d\u7cfb\u7d71\u7684\u5f71\u97ff\u3002\u57fa\u672c\u7cfb\u7d71\u7d93 \u518d\u5e73\u5747\u3002 \u884c \u7684\u96fb \u914d \u70ba B a s e l i n e S L A T D C C H T D C C A \u7531 Digit Error Rate (%) \u8def\u6cc1 0 km/h 50 km/h Without MLLR 0.28 0.58 0.41 0.56 90 km/h (19) Mic 1 + MLLR 29.0 31.7 33.4 With MLLR 0.50 0.79 0.63 0.77 53.4 Mic 3 51.0 54.8 58.7 \u4f86\u6c42\u51fa\u53d6\u6a23\u9ede\u4e0a\u7684\u4f4d b \u3002\u56e0\u70ba \u97f3\u7684\u901f\u5ea6 C \u548c \u7684\u9593\u8ddd d \u90fd\u662f\u56fa\u5b9a\u7684\uff0c\u56e0\u6b64\u6211\u5011\u8a2d\u8a08 Mic 2 + MLLR 25.5 29.9 33.1 \u8868\u4e5d\u3001SLA \u8207 TDCC \u884c\u901f\u5ea6\u4e4b\u6bd4\u8f03 (\u901f\u5ea6\u8a08\u7b97\u55ae\u4f4d\u70ba \u53e5)</td></tr><tr><td>\u8981\u7684\u4f5c\u7528\u662f\u5c07\u96fb \u4f9b\u61c9\u5668\u6240\u63d0\u4f9b\u7684\u96fb\u529b\u9032\u884c \u58d3\uff0c\u4e4b\u5f8c\u518d \u81f3 \u529b\uff0c\u4e26\u4fdd \u97f3\u6642\u8a0a \u7684 \u5b9a\uff0c\u4e26\u5c07\u8a0a \u81f3\u591a\u901a \u97f3 SigC31-4\u3002\u6b64\u5de5\u4f5c\u96fb\u8def\u662f \u63d0\u4f9b \u97f3\u6642\u6240\u9700\u7684\u96fb \u5206\u3002\u8a9e\u8005\u548c \u9663\u5217\u4ee5\u53ca \u97f3\u7684\u76f8\u5c0d\u4f4d \u5982\u5716\u4e03\u6240\u793a\u3002\u7e3d\u5171\u6709 15 \u4eba\u53c3\u8207 \u97f3\uff0c\u5305\u542b 12 \u4f4d Mic 4 46.5 53.0 57.2 Mic \u5e73\u5747 46.6 52.1 56.1 Mic 3 + MLLR 31.6 33.4 36.2 \u4e86\u4e00\u4e9b\u5be6\u9a57\u4f86 \u89e3\u53d6\u6a23\u983b\u7387\u5c0d SLA \u548c TDCC \u5169\u7a2e\u6f14\u7b97\u6cd5\u7684\u5f71\u97ff\u3002 Mic 4 + MLLR 28.3 31.4 34.5 \u751f\u548c 3 \u4f4d \u751f\uff0c\u6bcf\u4e00\u7a2e\u8def\u6cc1\u6709 30 \u53e5\u4e0d\u540c\u7684\u4e2d\u6587\u9023\u7e8c\u6578\u5b57\u3002\u6bcf\u7a2e\u8def\u6cc1\u7e3d\u5171 \u5f97 450 \u53e5\u97f3 \u3002 \u8868\u4e00\u3001\u57fa\u672c\u7cfb\u7d71\u7684\u8fa8\u8a8d\u7d50\u679c \u5be6\u9a57\u6642\u6211\u5011\u5148\u5c0d \u8a9e\u6599\u5229\u7528 \u5dee\u6cd5\u63d0\u9ad8\u53d6\u6a23\u983b\u7387\uff0c\u7d93\u7531 Delay-and-Sum Beamformer \u6c42 (Mic + MLLR)\u5e73\u5747 28.6 31.6 34.4 4. \u7d50\u8ad6</td></tr><tr><td>\u4f9d\u64da\u97f3 \u516c \u91dd\u5c0d\u96fb\u5bb9\u5f0f \u9023\u7e8c\u8a9e\u97f3\u8fa8\u8a8d\u6240\u4f7f\u7528\u7684\u6f14\u7b97\u6cd5\u70ba\u4e00\u968e\u6bb5\u6f14\u7b97\u6cd5\u3002\u5be6\u9a57\u7d50\u679c\u6211\u5011\u4ee5\u6578\u5b57\u932f\u8aa4\u7387(Digit Error Rate) \u7684\u5efa \u96fb\u8def \u52a0\u4fee\u6539\u5f8c\u7531\u6211\u5011\u81ea\u884c \u63a5 \u4f5c\u7684\u3002 \u4f86\u8868\u793a\u3002 \u51fa\u589e \u904e\u7684\u8a9e\u97f3\u8a0a \u5f8c\uff0c\u518d\u5c07\u53d6\u6a23\u983b\u7387 \u70ba 8KHz\u3002\u7136\u5f8c\u518d\u9032\u884c\u8fa8\u8b58\uff0c\u8fa8\u8a8d\u7d50\u679c\u5982\u8868\u56db(8KHz)\u3001 Mic \u5e73\u5747 46.6 52.1 56.1 \u672c\u8ad6\u6587\u4e2d\u6211\u5011\u5efa\u7acb\u4e00\u500b\u61c9\u7528 \u9663\u5217\u7684\u8a9e\u97f3\u8fa8\u8a8d\u7cfb\u7d71\uff0c\u6b64\u4e00\u7cfb\u7d71\u5229\u7528 Delay-and-Sum \u8def\u6cc1\uff0fDigit Error Rate (%)\uff0f\u89d2\u5ea6 30 60 90 120 150 0 km/h 35.2 31.9 60.6 58.6 55.4 \u8868\u4e03\u3001\u57fa\u672c\u7cfb\u7d71\u7d93\u7531MLLR\u8abf\u6574\u5f8c\u7684\u5be6\u9a57\u7d50\u679c \u8868\u4e94(16KHz)\u548c\u8868\u516d(24KHz)\u6240\u793a\u3002 Beamformer \u4f86 \u4f4e \u97f3\u5c0d\u65bc\u8a9e\u97f3\u8a0a \u7684\u5f71\u97ff\u3002\u540c\u6642\u6211\u5011\u4e5f\u63d0\u51fa\u4e86\u4e00\u500b\u61c9\u7528\u65bc \u9663\u5217</td></tr><tr><td>50 km/h \u6211\u5011\u53ef\u4ee5\u767c\u73fe SLA \u7684\u8fa8\u8a8d\u932f\u8aa4\u7387\u6709\u660e\u986f\u7684\u6539\u8b8a\uff0c\u53d6\u6a23\u983b\u7387\u7531 8KHz \u63d0\u9ad8\u81f3 16KHz \u548c 40.9 38.1 66.9 68.3 62.6 \u6f14\u7b97\u6cd5 Digit Error Rate (%) \u8def\u6cc1 0 km/h 50 km/h 90 km/h \u4e0a\u8a08\u7b97\u6642\u9593 \u7684\u6f14\u7b97\u6cd5 TDCC\u3002\u5be6\u9a57\u7684\u90e8\u5206\u6211\u5011\u9032\u884c\u4e86\u57fa\u672c\u7cfb\u7d71\u7684\u5be6\u9a57\u3001 \u5b9a\u5404\u7a2e\u4e0d\u540c\u89d2</td></tr><tr><td>90 km/h 24KHz \u6642\u932f\u8aa4\u7387\u5728 3 \u7a2e\u4e0d\u540c\u8def\u6cc1\u90fd\u6709\u986f\u8457\u7684\u4e0b \u3002\u800c\u63d0\u9ad8\u81f3 16KHz \u548c\u63d0\u9ad8\u81f3 24KHz \u76f8\u6bd4\u6642 42.8 40.4 70.0 69.6 65.7 (Mic + MLLR)\u5e73\u5747 28.6 31.6 34.4 \u5ea6\u7684\u5be6\u9a57\u3001\u53d6\u6a23\u983b\u7387\u6539\u8b8a\u7684\u5be6\u9a57\u3001\u4f7f\u7528 SLA \u6f14\u7b97\u6cd5\u3001\u4f7f\u7528\u6700\u5927\u80fd\u91cf\u97f3 \u7684 TDCC \u6f14\u7b97\u6cd5\u548c\u4f7f \u8868\u4e8c\u3001\u4e0d\u540c \u97f3 \u89d2\u5ea6\u4e0bDelay-and-Sum Beamformer\u7684\u8fa8\u8a8d\u7d50\u679c \u6f14\u7b97\u6cd5 Digit Error Rate (%) \u8def\u6cc1 0 km/h 50 km/h 90 km/h Mic \u5e73\u5747 46.7 52.1 56.1 \u56fa\u5b9a\u89d2\u5ea6 60 31.9 38.1 40.4 SLA 43.8 48.6 52.1 TDCC H 37.5 43.6 SLA + MLLR 29.9 31.5 35.1 \u5247\u5728 3 \u7a2e\u4e0d\u540c\u8def\u6cc1\u4e0a\u932f\u8aa4\u7387 \u6709\u4e9b\u8a31\u7684\u6539\u8b8a\u3002\u81f3\u65bc TDCC \u5247\u56e0\u70ba\u5176 \u7b97\u7684\u5c0d\u8c61\u5c31\u662f\u6642\u57df\u4e0a\u7684 \u53d6\u6a23\u9ede\uff0c\u56e0\u6b64\u8fa8\u8a8d\u932f\u8aa4\u7387\u4e26\u7121\u660e\u986f\u6539\u8b8a\u3002\u6b64\u4e00\u7d50\u679c\u986f\u793a\u7531\u65bc TDCC \u4e0d\u9700\u8981\u8a08\u7b97\u8a9e\u8005\u65b9\u5411\uff0c\u56e0 \u6b64\u53ef\u4ee5\u9069\u7528\u65bc\u5404\u7a2e\u53d6\u6a23\u983b\u7387\uff0c\u80fd \u4e00\u5b9a\u7684\u8fa8\u8a8d\u6548\u679c\u3002 \u6f14\u7b97\u6cd5 Digit Error Rate (%) \u8def\u6cc1 0 km/h 50 km/h TDCC H + MLLR 25.2 28.8 31.4 TDCC A + MLLR 21.1 24.9 28.2 \u8868\u516b\u3001SLA\u548cTDCC\u7d93\u7531MLLR\u8abf\u6574\u5f8c\u7684\u8fa8\u8a8d\u7d50\u679c\u6bd4\u8f03\u5716 \u7d93\u7531\u8868\u4e03\u7684\u5be6\u9a57\u7d50\u679c\u6211\u5011\u53ef\u4ee5\u767c\u73fe\uff0c\u57fa\u672c\u7cfb\u7d71\u4f7f\u7528 MLLR \u7684\u8a9e\u97f3\u6a21\u578b\u8abf\u6574\u6280\u8853\u5f8c\uff0c\u4e0d\u7ba1 \u7528\u5168\u90e8\u97f3 \u7684 \u672c\u8ad6\u6587\u4e2d\u4ea6\u7d50\u5408\u4e86\u8a9e\u97f3\u6a21\u578b\u8abf\u6574\u7684\u6280\u8853\u3002\u7d93\u7531\u5be6\u9a57\u6211\u5011\u53ef\u4ee5\u767c\u73fe\uff0c\u55ae\u7d14\u53ea\u4f7f\u7528 MLLR \u4f86 90 km/h 47.0 TDCC A 31.7 38.4 40.9 SLA H 43.79 48.64 52.12 TDCC H 37.50 43.58 47.03 \u8abf\u6574\u8a9e\u97f3\u6a21\u578b\u5373\u53ef\u7372\u5f97\u4e0d\u932f\u7684\u6548\u679c\u3002\u7136\u800c\u82e5\u5c07 \u9663\u5217\u548c\u8a9e\u97f3\u6a21\u578b\u8abf\u6574\u7684\u6280\u8853\u76f8\u7d50\u5408\uff0c\u5c0d \u5728 \u4e00\u7a2e\u8def\u6cc1\u90fd\u53ef\u6709\u6548\u7684 \u4f4e\u8fa8\u8a8d\u932f\u8aa4\u7387(0 \u65bc \u4e0b\u6240 \u65bc \u4f4e\u8fa8\u8a8d\u932f\u8aa4\u7387(\u5728\u4e0d\u540c\u8def\u6cc1\u4e0b\u5e73\u5747 \u53ef \u4f4e 25%\u7684\u8fa8\u8a8d\u932f\u8aa4\u7387)\u6703\u7522\u751f\u66f4\u986f\u8457\u7684\u6548\u679c\u3002\u5f9e \u8868\u4e09\u3001SLA\u548cTDCC\u8fa8\u8a8d\u7d50\u679c\u6bd4\u8f03\u5716 \u8868\u56db\u3001\u53d6\u6a23\u983b\u7387 8KHz \u6642 SLA \u548c TDCC \u7684\u8fa8\u8a8d\u7d50\u679c \u7684\u8a13\u7df4\u8a9e\u6599\u548c\u5229\u7528 \u9663\u5217\u65bc \u97f3 \u4e0b\u6240 \u7684 \u8a9e\u6599\u9593\u7684\u4e0d \u914d\u73fe\u8c61\u76f8\u7576 \u91cd\u3002 \u6211\u5011\u7814\u7a76\u7684\u7d50\u679c\uff0c\u53ef\u4ee5\u767c\u73fe\u4ecd\u7136\u9084\u6709\u8a31\u591a\u503c\u5f97\u7814\u7a76\u7684 \u984c\uff0c\u5982\u66f4 \u78ba\u8a9e\u8005\u65b9\u5411\u7684\u5b9a\u4f4d\u3001</td></tr><tr><td>\u7b2c\u4e8c\u7d44\u5be6\u9a57\u662f\u5c07\u6240 \u5f97\u7684 \u6f14\u7b97\u6cd5 Digit Error Rate (%) \u8def\u6cc1 \u8a9e\u6599\u5206\u5225\u7d93\u7531\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5\u548c TDCC \u6c42\u53d6\u4e0d\u540c 0 km/h 50 km/h 90 km/h \u5206\u6790\u8868\u516b\u7684\u7d50\u679c\uff0c\u6211\u5011\u767c\u73fe\u52a0\u5165\u8a9e\u97f3\u6a21\u578b\u8abf\u6574\u7684 SLA \u548c TDCC \u5728 \u4f4e\u8fa8\u8a8d\u932f\u8aa4\u7387\u4e0a\u4ea6\u6709 \u9593 \u4f4d \u7684\u8003\u91cf\u2026\u7b49\u3002\u672a\u4f86\u6211\u5011\u5c07\u4e3b\u8981\u81f4\u529b\u65bc\u7814\u7a76 \u9663\u5217\u4e2d \u7684 \u653e\u4f4d \u548c\u8fa8\u8a8d\u7387\u9593</td></tr><tr><td>\u5716\u4e03\u3001 \u97f3\u6642 \uff0c\u7d93\u904e\u88dc \u5f8c\u7522\u751f\u52a0 \u904e\u5f8c\u7684\u8a9e\u97f3\u8a0a \uff0c\u518d\u5206\u5225\u9032\u884c\u8fa8\u8a8d\uff0c\u5be6\u9a57\u7d50\u679c\u5982\u8868\u4e09\u6240\u793a\u3002 \u9663\u5217\u548c\u8a9e\u8005\u4ee5\u53ca \u97f3\u9593\u7684\u76f8\u5c0d\u4f4d \u5716 SLA H 34.94 39.97 42.00 \u986f\u8457\u7684\u6548\u679c\uff0c\u5728\u4e09\u7a2e\u4e0d\u540c\u8def\u6cc1\u4e0a TDCC \u7684\u6548\u80fd\u4ecd\u7136\u512a\u65bc SLA\u3002\u6700\u4f4e\u7684\u8fa8\u8a8d\u932f\u8aa4\u7387(21.10%)\u70ba \u7684\u6642\u9593 \u7684\u95dc\u4fc2\uff0c\u4ee5\u53ca\u5be6 \u5c07 \u9663\u5217\u7684\u6f14\u7b97\u6cd5\u61c9\u7528\u5728 \u6216\u6709\u56de\u97f3\u3001 \u97f3\u7684\u8a9e\u97f3\u8fa8\u8b58\u7cfb\u7d71\u4e0a\u3002</td></tr><tr><td>\u5716\u516d\u3001 3.3 Delay-and-Sum Beamformer\u5be6\u9a57\u7d50\u679c \u9663\u5217 \u97f3\u8a2d \u9023\u63a5\u5716 \u5176\u4e2d TDCC \u6709\u5169\u7a2e\u4e0d\u540c\u7684\u8a08\u7b97\u65b9\u6cd5\uff0cTDCC H \u8868\u793a\u6bcf\u4e00\u500b\u8a9e\u53e5 \u4f7f\u7528\u6700\u9ad8\u80fd\u91cf\u7684\u97f3 \u4f86\u8a08\u7b97 \u6642\u9593 \uff0c\u800c TDCC A \u5247\u8868\u793a\u6bcf\u4e00\u500b\u8a9e\u53e5\u7684\u6240\u6709\u97f3 \u7686\u88ab\u8003\u616e\u4f86\u8a08\u7b97\u6642\u9593 \u3002\u6b64\u5916\u8868\u4e09\u4ea6 TDCC H 36.90 42.69 47.09 \u8868\u4e94\u3001\u53d6\u6a23\u983b\u7387 16KHz \u6642 SLA \u548c TDCC \u7684\u8fa8\u8a8d\u7d50\u679c \u8def\u6cc1 0 km/h \u4e0b\u4f7f\u7528\u5168\u90e8\u97f3 \u4f86\u8a08\u7b97\u7684 TDCC \u6f14\u7b97\u6cd5\u3002</td></tr><tr><td>3. \u5be6\u9a57\u7d50\u679c 3.1 3.2 \u8a9e\u6599\u5eab \u5c0d\u65bc\u6bcf\u4e00\u500b \u5217\u51fa \u9663\u5217\u7684\u5e73\u5747\u8fa8\u8b58\u7387\u548c\u56fa\u5b9a\u89d2\u5ea6 60 \u6642\u7684\u8fa8\u8a8d\u932f\u8aa4\u7387\u4ee5\u65b9 \u6bd4\u8f03\u3002 (Mic1, Mic2, Mic3, Mic4)\u6240 \u96c6\u7684\u8a9e\u97f3\u8a0a \u5176\u500b\u5225\u7684\u5b57\u5143\u932f\u8aa4\u7387\u4ee5\u53ca \u6f14\u7b97\u6cd5 Digit Error Rate (%) \u8def\u6cc1 0 km/h 50 km/h 90 km/h 3.6 \u8fa8\u8a8d\u6642\u9593\u7684\u6bd4\u8f03 \u932f\u8aa4\u7387\u7684\u5e73\u5747\u503c\u5982\u8868\u4e00\u6240\u793a\uff0c\u6b64\u7d50\u679c\u53ef\u8996\u70ba\u57fa\u672c\u7cfb\u7d71(Baseline)\u7684\u932f\u8aa4\u7387\u3002\u5728\u6b64\u6211\u5011\u4f7f\u7528\u6240\u6709 \u89c0\u5bdf\u8868\u4e09\u7684\u8fa8\u8a8d\u7d50\u679c\u6bd4\u8f03\uff0c\u6211\u5011\u53ef\u4ee5\u767c\u73fe\u4f7f\u7528 Delay-and-Sum Beamformer \u7684 SLA \u548c SLA H 34.17 39.52 42.79 \u8fa8\u8a8d\u6642\u9593\u7684\u8a08\u7b97\u662f\u7d71\u8a08\u6240\u6709 \u8a9e\u6599(\u5171 1350 \u53e5\uff0c\u5e73\u5747\u4e00\u53e5\u5305\u542b 6 \u500b\u4e2d\u6587\u9023\u7e8c\u6578\u5b57)\u7d93\u7531 \u9663\u5217 \u97f3\u8a2d \u9663\u5217 \u97f3\u8a2d \u5982\u5716\u516d\u6240\u793a\uff0c\u4e3b\u8981\u7684\u90e8\u5206\u5305\u542b\u591a\u901a \u97f3 SigC31-4\u3001\u56db\u500b\u5168\u65b9\u5411 \u99ac\u53ef\u592b\u6a21\u578b\u4f86\u8868\u793a\uff0c\u6bcf\u4e00\u500b\u4e2d\u6587\u6578\u5b57\u4f7f\u7528 7 \u500b \uff0c \u97f3\u5247\u4f7f\u7528 3 \u500b \uff0c\u5206\u5225\u8868\u793a\u97f3 \u8fa8\u8a8d\u932f\u8aa4\u7387\u7684\u5e73\u5747\u503c\u4f5c\u70ba \u9663\u5217\u7684\u6574\u9ad4\u932f\u8aa4\u7387\u3002 TDCC \u78ba\u5be6\u80fd \u6709\u6548 \u4f4e\u932f\u8aa4\u7387\uff0c\u800c TDCC \u548c\u50b3\u7d71\u7684\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5 SLA \u76f8\u6bd4\uff0cTDCC \u66f4\u80fd TDCC H 38.27 44.08 49.07 \u8868\u516d\u3001\u53d6\u6a23\u983b\u7387 24KHz \u6642 SLA \u548c TDCC \u7684\u8fa8\u8a8d\u7d50\u679c \u6642\u9593 \u7684\u8a08\u7b97\u3001Delay-and-Sum Beamformer \u7684\u8655\u7406\u3001\u8a9e\u97f3\u7279\u5fb5\u53c3\u6578\u7684\u6c42\u53d6\u548c\u8a9e\u97f3\u8fa8\u8a8d\u7684\u6240 \u6211\u5011\u6240\u9032\u884c\u7684\u7b2c\u4e00\u7d44\u5be6\u9a57\u662f\u4e8b\u5148\u9810\u8a2d\u4e00\u4e9b \u97f3 \u89d2\u5ea6\u503c\u4f86\u9032\u884c\u5be6\u9a57\u4ee5 \u51fa\u6700\u4f73\u6548\u679c\u7684\u89d2 \u5ea6 \uff0c \u9019 \u88e1 \u6211 \u5011 \u5c07 \u97f3 \u7684 \u65b9 \u5411 \u56fa \u5b9a \u5f9e 30 \u5230 150 \u6bcf \u9593 \u9694 30 \u505a \u4e00 \u6b21 \u5be6 \u9a57 \uff0c \u518d \u5c0d \u7d93 \u7531 \u6709\u6548 \u4f4e\u8fa8\u8a8d\u932f\u8aa4\u7387\uff0c\u4e14 TDCC \u4f7f\u7528\u6240\u6709\u7684\u97f3 \u7684\u6548\u679c\u4e0d\u4f46\u6bd4\u4f7f\u7528\u4e00\u500b\u97f3 \u6548\u679c\u9084\u597d\uff0c\u800c\u4e14 \u6709\u6642\u9593\u518d\u505a\u5e73\u5747\u800c\u5f97\uff0c\u5be6\u9a57\u7d50\u679c\u5982\u8868\u4e5d\u6240\u793a\u3002\u57fa\u672c\u7cfb\u7d71\u5247 \u8a08\u7b97\u7279\u5fb5\u53c3\u6578\u548c\u8a9e\u97f3\u8fa8\u8a8d\u7684\u6642\u9593</td></tr></table>",
                "text": "\u662f\u7531 \u570b Signalogic \u516c \u6240\u751f\u7522\u7684\uff0c\u70ba\u4e00 4 \u500b\u901a \u7684 \u97f3 \uff0c\u4f7f \u7528\u7684\u6578\u4f4d\u8a0a \u8655\u7406 \u7247(DSP processor)\u70ba \u5668\u516c (TI)\u6240\u751f\u7522\u7684 TM8320C31\uff0c\u53ef\u540c\u6642\u63d0\u4f9b 4 \u500b\u901a \u9032\u884c \u97f3\u7684\u52d5\u4f5c\uff0c\u6b64 \u97f3 \u7684\u4ecb\u9762\u70ba ISA \u4ecb\u9762\u53ef \u65bc\u500b\u4eba\u96fb \u4e0a\uff0c\u4e26\u6709\u63d0\u4f9b D37 \u578b MLLR \u8abf\u6574\u5f8c\u7684\u5be6\u9a57\u7d50\u679c\u5982\u8868\u4e03\u6240\u793a\u3002\u6b64\u5916\uff0cSLA \u548c TDCC \u5206\u5225\u52a0\u4e0a MLLR \u7684\u5be6\u9a57\u7d50\u679c \u5982\u8868\u516b\u6240\u793a\u3002 km/h \u7531 46.64% \u81f3 28.61%\uff0c50 km/h \u7531 52.07% \u81f3 31.60%\uff0c90 km/h \u7531 56.12% \u81f3 34.42%)\uff0c\u5176\u539f\u56e0\u70ba\u4f7f\u7528\u50b3\u7d71 Pentium II 350 \u8655\u7406\u5668\u548c 128MB \u8a18 \u9ad4\u7684\u500b\u4eba\u96fb \uff0c\u4f5c\u696d\u7cfb \u7d71\u5247\u70ba Windows 98\u3002\u89c0\u5bdf\u5be6\u9a57\u7d50\u679c\uff0c\u6211\u5011\u767c\u73fe\u4e0d\u7ba1\u662f \u4f7f\u7528\u6700\u5927\u80fd\u91cf\u7684\u97f3 \u6216\u662f\u5168\u90e8\u97f3 \u7684 TDCC \u6f14\u7b97\u6cd5\u5728 \u884c\u901f\u5ea6\u4e0a\u7686\u512a\u65bc\u50b3\u7d71\u7684 SLA \u6f14\u7b97\u6cd5\u3002 TDCC \u6f14\u7b97\u6cd5\u4ee5\u53ca \u884c\u901f\u5ea6\u6bd4\u8f03\u3002\u7d93\u7531\u5be6\u9a57\u7d50\u679c\u6211\u5011\u53ef\u4ee5\u8b49\u660e TDCC \u7684\u6709\u6548\u6027 (\u5728\u4e0d\u540c\u8def\u6cc1\u4e0b\u5e73\u5747 \u53ef \u4f4e 15%\u7684\u8fa8\u8a8d\u932f\u8aa4\u7387)\u3002\u548c\u50b3\u7d71\u7684\u8a9e\u8005\u5b9a\u4f4d\u6f14\u7b97\u6cd5 SLA \u76f8\u6bd4\u8f03\uff0c TDCC \u4e0d\u8ad6\u662f\u5728\u8fa8\u8a8d\u932f\u8aa4\u7387 \u4f4e\u7684 \u5ea6\u4e0a\u6216 \u884c\u901f\u5ea6\u4e0a\u7686\u512a\u65bc SLA\u3002",
                "num": null,
                "html": null,
                "type_str": "table"
            }
        }
    }
}