|
{ |
|
"paper_id": "O04-1033", |
|
"header": { |
|
"generated_with": "S2ORC 1.0.0", |
|
"date_generated": "2023-01-19T08:00:23.431275Z" |
|
}, |
|
"title": "", |
|
"authors": [], |
|
"year": "", |
|
"venue": null, |
|
"identifiers": {}, |
|
"abstract": "", |
|
"pdf_parse": { |
|
"paper_id": "O04-1033", |
|
"_pdf_hash": "", |
|
"abstract": [], |
|
"body_text": [ |
|
{ |
|
"text": "( ) 1 _ _ , 1 j j C S C S j k k fs = \u220f (1) \uf961 Uni-gram , j k fs j \uf906 \uf961 k _ j C S j \uf906 \uf969 \uf961 ( ) 1 _ _ , 1 j j C W C W j k k fw = \u220f (2) \uf9f4\uf961 , j k fw j \uf906 k \uf961 _ j C W j \uf906 \uf969 ( ) ( ) 1 _ 1 _ _ _ , , 1 1 j j j C S C W C S C W j j k j k k k", |
|
"cite_spans": [], |
|
"ref_spans": [], |
|
"eq_spans": [], |
|
"section": "", |
|
"sec_num": null |
|
}, |
|
{ |
|
"text": "EQUATION", |
|
"cite_spans": [], |
|
"ref_spans": [], |
|
"eq_spans": [ |
|
{ |
|
"start": 0, |
|
"end": 8, |
|
"text": "EQUATION", |
|
"ref_id": "EQREF", |
|
"raw_str": "= = = \u00d7 \u220f \u220f j (3) \uf978 \uf9be \uf9ca 2 \uf978 \uf92d \uf906 \uf969 \uf906 \uf906 \uf906\ufa26 \uf901 \uf96b \uf9be \uf969 \ufa00 \uf92d \ufa26 \uf9a8 [11] \ufa00 \uf967 \uf9dd \uf978 \ufa00 \uf9dd \ufa08 \uf9dd \uf96b\uf969 \uf9dd \uf9dd \uf961 1. \uf9dd \uf937 \ufa08 \ufa00 \uf96b\uf969 26 \uf96b\uf969 12 MFCCs 12 MFCC s \uf97e delta energy \uf97e delta delta energy \uf969 150 \uf93f \uf9be \uf9dd syllable type Viterbi \uf9fa 2. \ufa00 \uf99a \uf918 \ufa00 \uf92d \uf9dd \uf97e energy \uf9b2\uf961 zero crossing rate \uf96b\uf969[11] \uf967 \uf92d 3. \uf99a \ufa00 \uf93f \ufa26 \ufa00 \uf961 \uf961 \uf967 ( ) | reject accept i i P X threshold Otherwise \u03bb \u23a7 < \u2192 \u23a8 \u2192 \u23a9 (4) i \u03bb \uf9be X \uf9f6 i threshold 3. \ufa01 3.1 \ufa01 \uf97e \uf9be [4][12] Phoneme Diphone (Demi-Syllable) (Syllable) \uf967 \ufa01 (Non-Uniform Unit) \uf92d \uf9ba \uf905 \ufa01 \ufa01 \uf99c \uf9b5 \uf906 \uf92d (1) (2) (3) (4) (5) (N) \uf967 \uf9b5 \uf974 \ufa01 \uf9ba \ufa01 \uf978 \uf9d0 \uf906 \uf906 \uf9d0 \uf906 syllable word \uf906 3 \uf967 \uf967 \ufa08 \uf9ba \ufa01 \ufa01 \uf97e \uf967 \uf906 \uf96b\uf969 \uf967 \uf9b5\uf92d\uf96f (A). \uf9b5 \uf977 \uf970 \uf9ba \uf94a (44.3ms) \uf977 (65.3ms) \uf9b5 \uf967 \uf978 \uf967 (B). \uf9b5 \uf9e8 \uf9ba (39.1ms) \uf92d \uf9ba (28ms) \uf9b5 \uf967 \uf967 \uf978 \ufa01 \uf9dd \uf961 \uf906 probabilistic syntactic parser \uf906 \uf9fa \uf9ba 4 1.) \uf967 2.)\uf9dd \uf9fa 3.) \uf97e \ufa01 3 \uf9d0 \uf906 4 \uf9b5 3.2 \uf961 \uf92d \uf9e4 \uf906 \uf9f7 \uf9fa \uf9dd \uf961 \uf906 PCFG , Probabilistic Context Free Grammar \uf92d \uf906 \ufa08 [5] \uf961 \uf906 \uf906 CFG, Context Free Grammar \uf92d \uf961 \uf92d \uf901 \uf906 CFG \uf961 \uf961 \uf906 \uf901 \ufa01\ufa09 \uf961 \uf906 \uf9a3 \uf9fc \uf9a3\uf9d0 \uf974 G 0 N \uf905 \uf99c 1, 1 2 , T W w w w T = \uf961 * 1, | T P S W G \u239b \u21d2 \u239c \u239d \u23a0 \u239e \u239f (5) * \uf937 \uf961 \uf961 \uf996 \uf9be \u21d2 A \u03b1 \u2192 \uf961 ( ) ( ) ( ) 1 | m j j i P A G C A C A \u03b1 \u03b1 = \u23a1 \u23a1 \u23a4 \u2192 = \u2192 \u2192 \u23a3 \u23a6 \u23a3 \u23a6 \u2211 i \u03b1 \u23a4 (6) \uf969 ( ) C i m i \u03b1 A \uf92d \uf969 Tree-Bank \uf961 PCFG Chomsky Normal Form \uf96f PCFG \uf9ea\uf97e \uf978 terminal term \uf961 1 i j N N N \u2192 + k l i N w \u2192 ( ) ( ) , | i j k i l j k l P N N N G P N w G \u2192 + \u2192 \u2211 \u2211 | 1 = (7) G 5 0 N \uf905 \uf99c 1, 1 2 , T W w w w T = \uf961 * * * 0 1 2 , 0 1 , 1 1 , | | T i m n m i n i P N w w w G P N W G P N W NW G \u2212 + \u239b \u239e \u239b \u239e \u239b \u239e\u239b \u21d2 = \u21d2 \u21d2 \u239c \u239f \u239c \u239f\u239c \u239c \u239f \u239d \u23a0 \u239d \u23a0\u239d \u239d \u23a0 \u2211 | T \u239e \u239f \u23a0 \u239e \u239f (8) (8) \uf961 Inside Probability \uf99c \uf961 \uf961 * , | i mn P N W G \u239b \u21d2 \u239c \u239d \u23a0 i N , m n m n W w w = ( ) , | i m n G \u03b2 Chomsky Normal Form \uf978 ( ) ( ) ( ) ( ) ( ) 1 * * * , , 1 , 1 , | , | | | | , | 1 , | n i mn i i j k j md k d n j k d m n i j k j k j k d m P N W G m n G P N N N G P N W G P N W G P N N N G m d G d n G \u03b2 \u03b2 \u03b2 \u2212 + = \u2212 = \u239b \u239e \u239b \u239e \u239b \u21d2 = = \u2192 \u21d2 \u21d2 \u239c \u239f \u239c \u239f \u239c \u239d \u23a0 \u239d \u23a0 \u239d = \u2192 + \u2211 \u2211 \u2211 \u2211 , | \u239e \u239f \u23a0 (9) 5 \uf961 \uf906 6 \uf961 \uf9f7 \uf9fa \uf969 \uf9fa \uf969 \uf961 ( ) ( ) ( ) ( ) ( ) ( ) max max max , , 1 , , , | | max | | |m ax | , | 1, | i i m n i j k j m d k d j k m d n i j k j k j k m d n m n G P N W G P N N N G P N W G P N W G P N N N G m d G d n G \u03b2 \u03b2 \u03b2 + \u2264 < \u2264 < \u239b \u239e \u239b \u239e \u239b \u239e \u239b = \u21d2 = \u2192 \u00d7 \u21d2 \u21d2 \u239c \u239f \u239c \u239f \u239c \u239c \u239f \u239d \u23a0 \u239d \u23a0 \u239d \u239d \u23a0 = \u2192 + , n \u239e \u239f \u23a0 \u239e \u239f w (10) (8) \uf961 Outside Probability \uf99c \uf978 \uf99c * 0 1 , 1 1 , | m j n T P N W N W G \u2212 + \u239b \u21d2 \u239c \u239d \u23a0 0 N 1, 1 1 1 m m W w w \u2212 \u2212 = 1, 1 n T n T W w + + = j N \uf961 \uf961 ( , | j m n G \u03b1 ) j N \uf961 i N ( ) ( ) ( ) * 0 1 , 1 1 , * 0 1, 1 1, 1, 1 1 * * , , 1 0 1, 1 1, 1 | , | | | | | q m j n T j T i j k m j d T k n d d n m i k i k j k dm d j n T d i j P N W N W G m n G P N N N G P N W N W G P N W P N N N G P N W P N W N W G P N N N \u03b1 \u2212 + \u2212 + + = + \u2212 \u2212 \u2212 + = \u239b \u239e \u21d2 = \u239c \u239f \u239d \u23a0 \u239b \u239e \u239b \u239e \u239b \u239e\u239b \u2192 \u00d7 \u21d2 \u21d2 \u239c \u239f \u239c \u239f\u239c \u239c \u239f \u239d \u23a0\u239d \u239d \u23a0 \u239c \u239f = \u239c \u239f \u239b \u239e \u239b \u239e \u239b \u239c \u239f + \u2192 \u00d7 \u21d2 \u21d2 \u239c \u239f \u239c \u239c \u239f \u239c \u239f \u239d \u23a0 \u239d \u239d \u23a0 \u239d \u23a0 \u2192 = \u2211 \u2211 \u2211 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) 1 1 , 1 | , | 1 , | | , 1| , | q T k i k d n m i k i k j k i d G m d G n d G P N N N G d m G d n G \u03b1 \u03b2 \u03b2 \u03b1 = + \u2212 = \u239b \u239e + \u239c \u239f \u239c \u239f \u239c \u239f + \u2192 \u2212 \u239c \u239f \u239d \u23a0 \u2211 \u2211 \u2211 * \u239e \u239f \u23a0 \u239e \u239f \u23a0 ) \u239e \u239f ) ) ) , +", |
|
"eq_num": "(11)" |
|
} |
|
], |
|
"section": "Score fs fw", |
|
"sec_num": null |
|
}, |
|
{ |
|
"text": "EQUATION", |
|
"cite_spans": [], |
|
"ref_spans": [], |
|
"eq_spans": [ |
|
{ |
|
"start": 0, |
|
"end": 8, |
|
"text": "EQUATION", |
|
"ref_id": "EQREF", |
|
"raw_str": "\uf9fa 11)", |
|
"eq_num": "( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ( ) max 0 1 , 1 1 , 1 , 1 1" |
|
} |
|
], |
|
"section": "Score fs fw", |
|
"sec_num": null |
|
}, |
|
{ |
|
"text": ", | |m", |
|
"cite_spans": [], |
|
"ref_spans": [], |
|
"eq_spans": [], |
|
"section": "Score fs fw", |
|
"sec_num": null |
|
}, |
|
{ |
|
"text": "EQUATION", |
|
"cite_spans": [], |
|
"ref_spans": [], |
|
"eq_spans": [ |
|
{ |
|
"start": 0, |
|
"end": 8, |
|
"text": "EQUATION", |
|
"ref_id": "EQREF", |
|
"raw_str": "ax | , | 1, | , max\u02c6m ax | , 1| , | q j m j n T i j k i k n d T j k i k j k i d m m n G P N W N W G P N N N G m d G n d G P N N N G d m G d n G \u03b1 \u03b1 \u03b2 \u03b2 \u03b1 \u2212 + + \u2264 \u2264 \u2264 \u2264 \u2212 \u239b \u239e = \u21d2 \u239c \u239f \u239d \u23a0 \u239b \u239e \u2192 + \u239c \u239f = \u239c \u239f \u239c \u239f \u2192 \u2212 \u239d \u23a0 (12) \uf967 \ufa01 \uf967 \uf99c \uf961 \uf967 \ufa00 \uf99c \uf99c w \uf961 \uf9d1 i N , m n m n W w w = * , , | i mn P N W w G \u239b \u21d2 \u239c \u239d \u23a0 ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( * , 1 , , | , , | , , | 1, | , , | , | 1, , | 1, , i mn i n j k i j k j k d m j k P N W w G m n w G m d w G d n G m d w P N N N G m d G d n w G d n w \u03b3 \u03b3 \u03b2 \u03b4 \u03b2 \u03b3 \u03b4 \u2212 = \u239b \u239e \u21d2 = \u239c \u239f \u239d \u23a0 \u239b \u239e \u239b \u239e + \u239c \u239f = \u2192 \u00d7 \u239c \u239f \u239c \u239f \u239c \u239f + + + \u239d \u23a0 \u239d \u23a0 \u2211 \u2211 (13) ( ) , 1, if is a substring of , , 0, otherwise m n w W m n w \u03b4 \u23a7 = \u23a8 \u23a9 (14) \uf9fa ( ) ( ) ( ) ( ) ( ( ) ( ) ( ) ( max , , , , | , || , , | 1 , | , , max\u02c6| , | 1, , | 1, , i i m n i j k j k j k m d n i j k j k m n w G P N W w G P N N N G m d w G d n G m d w P N N N G m d G d n w G d n w \u03b3 \u03b3 \u03b2 \u03b4 \u03b2 \u03b3 \u03b4 \u2264 < \u239b \u239e = \u21d2 \u239c \u239f \u239d \u23a0 \u239b \u239e \u2192 + \u239c \u239f = \u239c \u239f \u2192 + \u239d \u23a0 (15) 4. \uf9ea 4.1 \uf9ea \uf967 \uf967 \uf9ba \uf97e \uf9ea \uf961 \uf96a \uf967 4.1.1 \uf97e \uf906 \uf92d \uf969 \uf9be sparse data \uf9ba \uf967 \uf96a \uf97e Vector Space Model \uf97e \uf9be \uf97e \ufa01 R Q \u00d7 , R Q \u03a6 R PCFG G \uf969 Q \uf9be \uf906 \uf969 1 ,1 1 , 2 1 , 2 ,1 2 , 2 2 , ,1 , 2 , Q Q R Q R R R Q \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u00d7 \u23a1 \u23a4 \u23a2 \u23a5 = \u23a2 \u23a5 \u23a2 \u23a5 \u23a3 \u23a6 \u03a6 (16) , r q \u03c6 r \uf906 q q S , r q \u03c6 ( ) ( ) , 1 1 : , , r q r i j k T P Rule r N N N W w G \u03c6 \u03b5 = \u2212 \u2192 , | (17) \uf906 ( ) ( ) ( ) 1, 1, 1, , , : , , | , , , , i j k T i j k T a b c T a b c P Rule r N N N W w G C N N N W w C N N N W w \u2192 = \u2192 \u2192 \u2211 (18) \uf92d\ufa01\uf97e \uf9be \uf9dd \uf97e\ufa01 \uf91b\ufa01 Entropy \uf97e\ufa01 \uf9be (", |
|
"eq_num": ") ( ) ( ) ( ) ( ) ( ( ) ( )" |
|
} |
|
], |
|
"section": "Score fs fw", |
|
"sec_num": null |
|
}, |
|
{ |
|
"text": "EQUATION", |
|
"cite_spans": [], |
|
"ref_spans": [], |
|
"eq_spans": [ |
|
{ |
|
"start": 0, |
|
"end": 8, |
|
"text": "EQUATION", |
|
"ref_id": "EQREF", |
|
"raw_str": ") 1, 1, 1 1, 1, 1 1 , 1 log log , , q a a q Q i j k T i j k T r Q Q a a q i j k T i j k T a a C N N N W C N N N W Q C N N N W C N N N W \u03b5 = = = \u239b \u239e \u239c \u239f \u2192 \u2192 \u239c \u239f = \u2212 \u239c \u239f \u2192 \u2192 \u239c \u239f \u239d \u23a0 \u2211 \u2211 \u2211 , q q q T (19) \uf9be \uf906 \uf906 \ufa01 ( ) ( ) ( ) 1, 1 q q q q T W w w = q q T ( ) ( ) 1, , q q i j k T C N N N W \u2192 q \uf906 \uf969 i j N N N \u2192 k ) \u00d7 \u00d7\u00d7 4.1.2 \uf9ea \uf96a \uf96a LSI, Latent Semantic Indexing \uf967 \uf901 \ufa09 \uf97e \ufa01 \uf96a \uf962 \uf962 \uf9cd \uf962 \uf9b5 \ufa01 \uf97e \ufa01 \uf98a \uf9cd \uf969 \uf9cd 98% \uf962\uf97e ( ( ) 1,1 1,2 1, T 2 ,1 2 ,2 2 ,", |
|
"eq_num": ",1 ,2 ," |
|
} |
|
], |
|
"section": "Score fs fw", |
|
"sec_num": null |
|
}, |
|
{ |
|
"text": "w here min , 0 0 0 1 1 1 1 2 1 arg min , , , ", |
|
"cite_spans": [], |
|
"ref_spans": [ |
|
{ |
|
"start": 13, |
|
"end": 38, |
|
"text": "0 0 0 1 1 1 1 2 1", |
|
"ref_id": null |
|
} |
|
], |
|
"eq_spans": [], |
|
"section": "Score fs fw", |
|
"sec_num": null |
|
}, |
|
{ |
|
"text": "EQUATION", |
|
"cite_spans": [], |
|
"ref_spans": [], |
|
"eq_spans": [ |
|
{ |
|
"start": 0, |
|
"end": 8, |
|
"text": "EQUATION", |
|
"ref_id": "EQREF", |
|
"raw_str": "Q Q R Q R n n n Q n R R RQ n R Q \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u03c6 \u00d7 \u23a1 \u23a4 \u23a2 \u23a5 = = \u23a2 \u23a5 \u23a2 \u23a5 \u23a3 \u23a6 = \u03a6 T S D (20) ( ) T 1 1 where , min 98% k n R Q R d d d Q d i i k i i d n d \u03bb \u03bb \u00d7 \u00d7 \u00d7 \u00d7 = = \u239b \u239e = < = \u239c \u239f \u239d \u23a0 \u2211 \u2211 \u03a6 T S D > (21) \uf962 \uf9dd R d \u00d7 T \uf978 \uf906 \uf97e \ufa01 \uf97e \uf906 x \uf906 w y \uf9dd \uf9ea ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) T T 0 T T ( , ) log 1, , , | w w R d R d q w w q q w w R d R d q SyntacticCost T q w G \u03b3 \u00d7 \u00d7 \u00d7 \u00d7 \u239b \u239e \u00d7 \u00d7 \u239c \u239f = \u2212 \u00d7 \u239c \u239f \u00d7 \u00d7 \u00d7 \u239c \u239f \u239d \u23a0 T x T y x y T x T y i (22) 4.2 \ufa01 \uf9ba \uf967 \ufa01 \ufa01 \uf9dd \uf906 \uf906 \uf9e4 \uf9d8 4.2.1 \ufa01 \ufa01 \uf97e \uf99a \uf978 \uf967\uf99a \ufa01 \uf905 256 FFT Fast Fourier Transform \uf97e \uf92d \uf967 \uf9dd Linear Regression \uf99a \uf97e \uf99a \uf978 \uf961 2 1 1 1 ( , ) ( )[ ( ) ( )] k n n n n i SD u u w i u i u i + + = = \u2206 \u2212\u2206 \u2211 (23) \uf97e \uf99a \uf978 \uf9dd Autocorrelation \uf97e \uf978 \uf962 \ufa01 \uf97e \uf9dd \uf978 \uf97e \uf97e \ufa01 \uf978 \ufa01 \ufa01 1 0 1 ( , )", |
|
"eq_num": "( , ) ( ," |
|
} |
|
], |
|
"section": "Score fs fw", |
|
"sec_num": null |
|
} |
|
], |
|
"back_matter": [], |
|
"bib_entries": { |
|
"BIBREF0": { |
|
"ref_id": "b0", |
|
"title": "The AT&T Next-Generation TTS System", |
|
"authors": [ |
|
{ |
|
"first": "M", |
|
"middle": [], |
|
"last": "Beutnagel", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "A", |
|
"middle": [], |
|
"last": "Conkie", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "J", |
|
"middle": [], |
|
"last": "Schroeter", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "Y", |
|
"middle": [], |
|
"last": "Stylianou", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "A", |
|
"middle": [], |
|
"last": "Syrdal", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 1998, |
|
"venue": "Proc. of ICSLP'98", |
|
"volume": "", |
|
"issue": "", |
|
"pages": "931--934", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "M. Beutnagel, A. Conkie, J. Schroeter, Y. Stylianou, and A. Syrdal, \"The AT&T Next-Generation TTS System,\" in Proc. of ICSLP'98, Sydney, Australia, pp. 931-934,1998", |
|
"links": null |
|
}, |
|
"BIBREF1": { |
|
"ref_id": "b1", |
|
"title": "Corpus-Based Unit Selection for Natural-Sounding Speech Synthesis", |
|
"authors": [ |
|
{ |
|
"first": "Jon Rong Wei", |
|
"middle": [], |
|
"last": "Yi", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 2003, |
|
"venue": "", |
|
"volume": "", |
|
"issue": "", |
|
"pages": "", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "Jon Rong Wei Yi, Corpus-Based Unit Selection for Natural-Sounding Speech Synthesis, Ph.D. thesis, Massachusetts Institute of Technology, 2003", |
|
"links": null |
|
}, |
|
"BIBREF2": { |
|
"ref_id": "b2", |
|
"title": "An Introduction to Text-to-Speech Synthesis", |
|
"authors": [ |
|
{ |
|
"first": "T", |
|
"middle": [], |
|
"last": "Dutoit", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 1997, |
|
"venue": "Text, Speech and Language Technology", |
|
"volume": "3", |
|
"issue": "", |
|
"pages": "", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "T. Dutoit, Text, Speech and Language Technology. vol.3: An Introduction to Text-to-Speech Synthesis., Kluwer Academic Publishers, Dordrecht, 1997", |
|
"links": null |
|
}, |
|
"BIBREF3": { |
|
"ref_id": "b3", |
|
"title": "Tree-based Unit Selection for English Speech Synthesis", |
|
"authors": [ |
|
{ |
|
"first": "W", |
|
"middle": [ |
|
"J" |
|
], |
|
"last": "Wang", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "W", |
|
"middle": [ |
|
"N" |
|
], |
|
"last": "Campbell", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "N", |
|
"middle": [], |
|
"last": "Iwahashi", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "Y", |
|
"middle": [], |
|
"last": "Sagisaka", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 1993, |
|
"venue": "Proc. of ICASSP'93", |
|
"volume": "2", |
|
"issue": "", |
|
"pages": "191--194", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "W. J. Wang, W. N. Campbell, N. Iwahashi and Y. Sagisaka, \"Tree-based Unit Selection for English Speech Synthesis,\" in Proc. of ICASSP'93, Minneapolis, MN, vol.2, pp. 191-194, Apr. 1993", |
|
"links": null |
|
}, |
|
"BIBREF4": { |
|
"ref_id": "b4", |
|
"title": "Spoken Language Processing", |
|
"authors": [ |
|
{ |
|
"first": "X", |
|
"middle": [], |
|
"last": "Huang", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "A", |
|
"middle": [], |
|
"last": "Acero", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "H", |
|
"middle": [ |
|
"W" |
|
], |
|
"last": "Hon", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 2001, |
|
"venue": "", |
|
"volume": "", |
|
"issue": "", |
|
"pages": "133--190", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "X. Huang, A. Acero and H. W. Hon, Spoken Language Processing, pp. 133-190, Prentice Hall, 2001", |
|
"links": null |
|
}, |
|
"BIBREF5": { |
|
"ref_id": "b5", |
|
"title": "Measures of Emotion", |
|
"authors": [ |
|
{ |
|
"first": "J", |
|
"middle": [ |
|
"A" |
|
], |
|
"last": "Russell", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 1989, |
|
"venue": "Emotion Theory, Research, and Experience", |
|
"volume": "", |
|
"issue": "", |
|
"pages": "83--111", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "J.A. Russell, \"Measures of Emotion,\" in R. Plutchik and H. Kellerman (Eds.), Emotion Theory, Research, and Experience. pp. 83-111, Academic Press, N.Y., 1989", |
|
"links": null |
|
}, |
|
"BIBREF6": { |
|
"ref_id": "b6", |
|
"title": "A Study on Corpus-based Speech Synthesis with Emotion", |
|
"authors": [ |
|
{ |
|
"first": "A", |
|
"middle": [], |
|
"last": "Iida", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 2002, |
|
"venue": "", |
|
"volume": "", |
|
"issue": "", |
|
"pages": "", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "A. Iida, \"A Study on Corpus-based Speech Synthesis with Emotion,\" Doctor of Media and Governance thesis, Graduate School of Media and Governance, Keio University, Sep. 2002", |
|
"links": null |
|
}, |
|
"BIBREF7": { |
|
"ref_id": "b7", |
|
"title": "Experiments with Emotive Speech, Acted Utterances and Synthesized Replicas", |
|
"authors": [ |
|
{ |
|
"first": "R", |
|
"middle": [], |
|
"last": "Carlson", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "G", |
|
"middle": [], |
|
"last": "Granstrom", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "L", |
|
"middle": [], |
|
"last": "Nord", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 1992, |
|
"venue": "Speech Communication", |
|
"volume": "2", |
|
"issue": "", |
|
"pages": "347--355", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "R. Carlson, G. Granstrom and L. Nord, \"Experiments with Emotive Speech, Acted Utterances and Synthesized Replicas,\" Speech Communication, vol. 2, pp.347-355, 1992", |
|
"links": null |
|
}, |
|
"BIBREF8": { |
|
"ref_id": "b8", |
|
"title": "The emotions", |
|
"authors": [ |
|
{ |
|
"first": "N", |
|
"middle": [], |
|
"last": "Frijda", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 1986, |
|
"venue": "", |
|
"volume": "", |
|
"issue": "", |
|
"pages": "", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "N. Frijda, The emotions, Cambridge University Press, N.Y., 1986", |
|
"links": null |
|
}, |
|
"BIBREF9": { |
|
"ref_id": "b9", |
|
"title": "Communication and Emotion: Basic Concepts and Approaches", |
|
"authors": [ |
|
{ |
|
"first": "L", |
|
"middle": [ |
|
"K" |
|
], |
|
"last": "Guerrero", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "P", |
|
"middle": [ |
|
"A" |
|
], |
|
"last": "Andersen", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "M", |
|
"middle": [ |
|
"R" |
|
], |
|
"last": "Trost", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 1998, |
|
"venue": "Handbook of Communication and Emotion: Research, Theory, Applications, and Contexts", |
|
"volume": "", |
|
"issue": "", |
|
"pages": "3--27", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "L. K. Guerrero, P. A. Andersen and M. R. Trost, \"Communication and Emotion: Basic Concepts and Approaches,\" in P. A. Andersen and L. K. Guerrero (Eds.), Handbook of Communication and Emotion: Research, Theory, Applications, and Contexts, pp. 3-27. Academic Press, San Diego, 1998", |
|
"links": null |
|
}, |
|
"BIBREF10": { |
|
"ref_id": "b10", |
|
"title": "Automatic Speech Segmentation and Verification for Concatenative Synthesis", |
|
"authors": [ |
|
{ |
|
"first": "C", |
|
"middle": [ |
|
"C" |
|
], |
|
"last": "Kuo", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "C", |
|
"middle": [ |
|
"S" |
|
], |
|
"last": "Kuo", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "J", |
|
"middle": [ |
|
"H" |
|
], |
|
"last": "Chen", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "S", |
|
"middle": [ |
|
"C" |
|
], |
|
"last": "Chang", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 2003, |
|
"venue": "Proc. of Eurospeech'03", |
|
"volume": "", |
|
"issue": "", |
|
"pages": "", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "C. C. Kuo, C. S. Kuo, J. H. Chen and S. C. Chang, \"Automatic Speech Segmentation and Verification for Concatenative Synthesis,\" in Proc. of Eurospeech'03, Geneva, Switzerland, 2003", |
|
"links": null |
|
}, |
|
"BIBREF11": { |
|
"ref_id": "b11", |
|
"title": "Selecting Non-uniform Units from a Very Large Corpus for Concatenative Speech Synthesizer", |
|
"authors": [ |
|
{ |
|
"first": "M", |
|
"middle": [], |
|
"last": "Chu", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "H", |
|
"middle": [], |
|
"last": "Peng", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "H", |
|
"middle": [ |
|
"Y" |
|
], |
|
"last": "Yang", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "E", |
|
"middle": [], |
|
"last": "Chang", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 2001, |
|
"venue": "Proc. of ICASSP'01", |
|
"volume": "2", |
|
"issue": "", |
|
"pages": "785--788", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "M. Chu, H. Peng, H. Y. Yang and E. Chang, \"Selecting Non-uniform Units from a Very Large Corpus for Concatenative Speech Synthesizer,\" in Proc. of ICASSP'01, vol. 2, pp.785-788, Salt Lake City, Utah, U.S.A., 2001", |
|
"links": null |
|
}, |
|
"BIBREF12": { |
|
"ref_id": "b12", |
|
"title": "Automatic Generation of Synthesis Units and Prosodic Information for Chinese Concatenative Synthesis", |
|
"authors": [ |
|
{ |
|
"first": "C", |
|
"middle": [ |
|
"H" |
|
], |
|
"last": "Wu", |
|
"suffix": "" |
|
}, |
|
{ |
|
"first": "J", |
|
"middle": [ |
|
"H" |
|
], |
|
"last": "Chen", |
|
"suffix": "" |
|
} |
|
], |
|
"year": 2001, |
|
"venue": "Speech Communication", |
|
"volume": "35", |
|
"issue": "", |
|
"pages": "219--237", |
|
"other_ids": {}, |
|
"num": null, |
|
"urls": [], |
|
"raw_text": "C. H. Wu and J. H. Chen, \"Automatic Generation of Synthesis Units and Prosodic Information for Chinese Concatenative Synthesis,\" Speech Communication, vol.35, pp.219-237, 2001", |
|
"links": null |
|
} |
|
}, |
|
"ref_entries": {} |
|
} |
|
} |