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Datasets:
JST-SUPERB
/
MUSAN-music_encodec_24k_6bps

Modalities:
Audio
Text
Formats:
parquet
Size:
1K - 10K
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speech_input
stringlengths
0
425
noisy_-20dB
audioduration (s)
0.08
41
noisy_10dB_transcription_whisper-small.en
stringlengths
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913
noisy_5dB_transcription_whisper-small.en
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912
noisy_0dB_transcription_whisper-small.en
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1.24k
noisy_-5dB_transcription_whisper-small.en
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2.15k
noisy_-10dB_transcription_whisper-small.en
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2.63k
noisy_10dB_transcription_whisper-medium.en
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898
noisy_5dB_transcription_whisper-medium.en
stringlengths
3
404
noisy_0dB_transcription_whisper-medium.en
stringlengths
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1.34k
noisy_-5dB_transcription_whisper-medium.en
stringlengths
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2.66k
noisy_-10dB_transcription_whisper-medium.en
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2.22k
noisy_10dB_transcription_whisper-large-v3
stringlengths
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404
noisy_5dB_transcription_whisper-large-v3
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404
noisy_0dB_transcription_whisper-large-v3
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noisy_-5dB_transcription_whisper-large-v3
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1.48k
noisy_-10dB_transcription_whisper-large-v3
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2.66k
output
stringlengths
1
2.92k
clean_audio_transcription_whisper-small.en
stringlengths
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404
clean_audio_transcription_whisper-medium.en
stringlengths
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clean_audio_transcription_whisper-large-v3
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clean_audio_unit
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sequencelengths
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noisy_-10dB_unit
sequencelengths
8
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Categorize the following sentence: The car is red.
Categorize the following sentence. The car is red.
Categorize the following sentence. The car is red.
Categorize the following sentence. The car is red.
Categorize the following sentence. The car is red.
I got back
Categorize the following sentence, the car is red.
Categorize the following sentence. The car is red.
Categorize the following sentence. The car is red.
Categorize the following sentence. The car is red.
I'm gonna go back to the one with the same voice.
Categorize the following sentence, the car is red.
Categorize the following sentence, the car is red.
Categorize the following sentence, the car is red.
Categorize the following sentence, the car is red.
I had to go back for two days and one night. I had to go back.
Category: Descriptive Sentence.
Categorize the following sentence. The car is red.
Categorize the following sentence, the car is red.
Categorize the following sentence, The car is red.
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Construct a metaphor that captures the feeling of joy.
Construct the metaphor that captures the feeling of joy.
Construct the metal form that captures the feeling of joy.
Construct men so that it captures the feeling of joy.
Construct mental that captures the feeling of joy.
He's got the answer.
Construct the metaphor that captures the feeling of joy.
Construct the metaphor that captures the feeling of joy.
Construct mental that captures the feelings joy
Construct Megatron captures this feeling of joy.
I'm just a little kid.
Construct a metaphor that captures the feeling of joy.
Construct a metaphor that captures the feeling of joy.
Construct metaphor that captures the feeling of joy.
Constructing that instrument captures the feeling of joy.
I'm sorry.
Joy is like a bountiful garden, where vibrant flowers bloom and sweet fragrances fill the air, where bees buzz and birds sing, and where each step taken fills the heart with warmth and happiness.
Construct the metaphor that captures the feeling of joy.
Construct the metaphor that captures the feeling of joy.
Construct a metaphor that captures the feeling of joy.
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Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name 3 things that a computer can do that a person cannot.
Name 3 things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
1. Perform complex calculations at a high speed: Computers can perform millions of mathematical operations in a fraction of a second, much faster than any human could. Tasks such as statistical analysis, financial modeling, and other data-driven tasks can be done quickly and accurately using a computer. 2. Store and retrieve vast amounts of information: Computers have the ability to store a large amount of data and can retrieve it almost instantly. This is much faster and more efficient than a human trying to remember or search for information. 3. Run multiple tasks simultaneously: Computers can multitask and run multiple programs and operations at the same time. This allows them to perform a variety of tasks at the same time, while a human can typically only focus their attention on one task at a time.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
Name three things that a computer can do that a person cannot.
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939, 135, 584, 969, 28, 430, 19, 578, 985, 291, 59, 189, 255, 28, 466, 403, 459, 384, 458, 314, 1007, 915, 138, 450, 305, 137, 99, 58, 918, 140, 299, 239, 915, 64, 524, 736, 725, 342, 667, 941, 443, 531, 452, 113, 937, 200, 140, 999, 805, 965, 15, 981, 827, 905, 116, 777, 847, 1022, 406, 366, 1019, 985, 975, 319, 601, 319, 457, 362, 395, 274, 64, 381, 474, 1016, 381, 917, 138, 589, 248, 708, 937, 228, 427, 299, 195, 233, 202, 369, 894, 558, 811, 965, 336, 595, 456, 164, 325, 836, 40, 570, 313, 416, 1020, 1016, 25, 372, 512, 742, 384, 109, 770, 372, 431, 739, 549, 704, 251, 620, 784, 759, 47, 896, 799, 439, 142, 294, 479, 39, 804, 983, 844, 40, 198, 384, 170, 652, 638, 325, 22, 64, 537, 153, 649, 652, 495, 827, 354, 737, 948, 491, 632, 843, 575, 842, 584, 986, 927, 708, 8, 78, 488, 167, 515, 301, 596, 268, 919, 215, 500, 85, 10, 976, 667, 1018, 919, 1007, 887, 268, 40, 784, 131, 347, 653, 173, 857, 414, 324, 823, 651, 388, 195, 842, 134, 265, 632, 611, 673, 384, 285, 534, 621, 672, 784, 621, 523, 1020, 976, 938, 815, 807, 986, 464, 999, 431, 847, 21, 536, 1006, 1006, 903, 743, 521, 441, 708, 855, 7, 510, 740, 266, 55, 432, 1020, 934, 245, 325, 891, 211, 778, 475, 1007, 59, 259, 189, 200, 984, 694, 443, 919, 176 ], [ 262, 863, 673, 602, 546, 1020, 937, 1004, 614, 581, 379, 962, 299, 684, 407, 455, 809, 516, 835, 97, 511, 900, 254, 739, 371, 759, 459, 541, 740, 861, 304, 343, 96, 614, 785, 975, 897, 186, 531, 856, 576, 213, 298, 147, 116, 257, 671, 377, 95, 748, 908, 858, 768, 946, 851, 205, 348, 1006, 153, 182, 1019, 394, 498, 356, 880, 378, 661, 336, 376, 222, 113, 72, 230, 531, 623, 262, 230, 195, 531, 233, 216, 104, 106, 104, 158, 218, 115, 5, 667, 323, 728, 313, 179, 738, 619, 458, 608, 285, 390, 346, 897, 923, 559, 437, 343, 629, 800, 144, 402, 416, 948, 415, 833, 705, 641, 460, 941, 970, 182, 180, 594, 867, 97, 306, 161, 148, 912, 920, 27, 214, 213, 884, 636, 912, 683, 429, 234, 534, 592, 224, 997, 279, 172, 245, 937, 673, 188, 906, 711, 12, 665, 942, 913, 800, 407, 280, 341, 758, 115, 330, 875, 323, 416, 132, 733, 424, 106, 1008, 132, 953, 432, 601, 596, 262, 705, 222, 765, 422, 431, 399, 502, 9, 3, 390, 485, 146, 16, 465, 651, 959, 908, 955, 233, 555, 535, 253, 1016, 48, 222, 378, 407, 400, 645, 855, 874, 772, 418, 195, 418, 95, 959, 166, 148, 884, 685, 286, 225, 515, 759, 176, 313, 959, 998, 245, 139, 434, 455, 568, 95, 21, 661, 36, 364, 872, 177, 397, 801, 120, 120, 971, 358, 343, 923, 981, 334, 577, 234, 552, 601, 602, 817, 931, 792 ], [ 489, 389, 786, 801, 942, 835, 834, 60, 293, 355, 943, 199, 454, 74, 174, 25, 538, 520, 369, 533, 19, 919, 734, 391, 846, 452, 669, 290, 959, 410, 350, 312, 34, 756, 694, 104, 694, 831, 786, 411, 581, 939, 933, 190, 976, 752, 425, 549, 470, 351, 792, 315, 744, 628, 327, 895, 743, 123, 224, 488, 563, 423, 589, 932, 357, 538, 421, 411, 767, 36, 424, 301, 879, 319, 257, 822, 529, 524, 327, 475, 367, 530, 948, 32, 817, 532, 668, 186, 379, 890, 232, 69, 85, 38, 714, 327, 464, 849, 939, 995, 942, 137, 163, 861, 879, 528, 993, 444, 335, 261, 533, 481, 820, 280, 477, 942, 567, 302, 524, 243, 411, 350, 78, 643, 821, 643, 672, 734, 491, 770, 173, 327, 60, 410, 381, 721, 327, 486, 202, 242, 988, 260, 615, 883, 459, 151, 905, 340, 572, 903, 241, 753, 337, 133, 25, 443, 443, 920, 920, 1009, 34, 800, 45, 758, 522, 786, 345, 567, 446, 544, 711, 329, 361, 963, 489, 119, 290, 442, 654, 181, 782, 998, 933, 258, 753, 585, 824, 968, 49, 938, 435, 454, 615, 971, 313, 347, 788, 261, 261, 995, 605, 493, 533, 339, 177, 605, 201, 949, 312, 963, 14, 723, 974, 885, 890, 238, 824, 198, 86, 639, 776, 1022, 744, 369, 315, 151, 316, 229, 67, 992, 243, 287, 381, 773, 808, 289, 833, 189, 186, 951, 552, 831, 758, 360, 772, 944, 936, 506, 764, 867, 125, 380, 1010 ], [ 832, 559, 897, 670, 475, 315, 12, 514, 615, 965, 154, 522, 157, 218, 1017, 257, 895, 284, 982, 677, 738, 324, 254, 410, 506, 997, 879, 824, 770, 434, 758, 768, 12, 670, 834, 418, 19, 921, 688, 372, 624, 502, 897, 189, 897, 344, 736, 462, 542, 1000, 568, 1013, 1018, 402, 439, 13, 13, 276, 916, 127, 1008, 432, 268, 1007, 682, 541, 788, 239, 897, 107, 832, 607, 924, 395, 912, 344, 933, 658, 642, 940, 110, 698, 5, 886, 763, 15, 792, 832, 733, 192, 473, 16, 804, 979, 395, 693, 16, 476, 1000, 516, 322, 401, 429, 748, 410, 590, 936, 793, 413, 903, 1022, 180, 180, 311, 761, 830, 983, 19, 570, 804, 552, 936, 551, 853, 592, 446, 601, 843, 660, 551, 439, 652, 470, 1018, 851, 590, 388, 728, 733, 782, 1021, 785, 506, 225, 495, 337, 608, 922, 63, 366, 215, 288, 705, 303, 627, 364, 685, 291, 1001, 411, 743, 647, 555, 768, 307, 334, 229, 507, 780, 561, 89, 350, 384, 810, 897, 477, 358, 595, 559, 824, 189, 516, 855, 516, 505, 280, 565, 848, 595, 541, 996, 922, 622, 203, 16, 890, 13, 296, 346, 283, 8, 671, 766, 591, 509, 1020, 479, 930, 1001, 758, 279, 199, 495, 707, 550, 404, 256, 751, 488, 514, 697, 945, 998, 688, 753, 167, 554, 922, 938, 133, 283, 115, 735, 614, 335, 723, 36, 383, 530, 651, 927, 279, 976, 638, 806, 845, 315, 473, 283, 965, 149, 965, 935 ] ]
Describe what is meant by computing power.
Describe what is meant by computing power.
Describe what is meant by computing power.
Describe what is meant by computing power
Describe what was meant by computing power.
This is way, way, way, way
Describe what is meant by computing power.
Describe what is meant by computing power.
Describe what is meant by computing power.
Describe what was meant by computing power.
This is how I look like a pitting power.
Describe what is meant by computing power.
Describe what is meant by computing power.
Describe what is meant by computing power.
Describe what is meant by computing power.
This is what is meant by computing power.
"Computing power refers to the capacity of a computer to process information and perform calculation(...TRUNCATED)
Describe what is meant by computing power.
Describe what is meant by computing power.
Describe what is meant by computing power.
[[121,408,62,62,724,875,549,816,701,681,813,847,934,574,744,574,574,496,798,798,537,408,410,780,11,1(...TRUNCATED)
[[537,604,126,999,402,533,549,109,701,681,813,847,934,574,744,574,496,496,409,409,499,393,957,900,49(...TRUNCATED)
[[740,260,731,303,640,497,496,109,701,681,813,847,934,125,744,125,125,549,461,409,499,791,23,23,275,(...TRUNCATED)
[[511,38,791,276,274,731,549,109,701,924,689,624,513,125,744,125,496,207,386,789,59,367,602,731,293,(...TRUNCATED)
[[961,511,586,511,891,366,366,109,657,664,150,109,7,390,64,71,64,624,814,640,541,694,713,637,541,108(...TRUNCATED)
[[142,303,7,303,480,207,329,440,657,924,13,711,624,178,64,342,97,181,1020,844,814,231,152,730,366,84(...TRUNCATED)
List 10 important events in the history of the US.
List 10 Important Events in the History of the US
List 10 important events in the history of the US.
list 10 important events in the history of the US.
10 important events in the history of the US
List ten important events in the history of New Zealand
list 10 important events in the history of the US.
list 10 important events in the history of the US.
list 10 important events in the history of the US.
list 10 important events in the history of the US.
list 10 important events in the history of the universe.
List 10 important events in the history of the US
List 10 important events in the history of the US
List 10 Important Events in the History of the US
List 10 Important Events in the History of the US
List 10 important events in the history of the U.S.
"1. The Signing of the Declaration of Independence (1776): On July 4th, 1776, the 13 British colonie(...TRUNCATED)
List 10 Important Events in the History of the US
List 10 Important Events in the History of the US
List 10 Important Events in the History of the US
[[121,408,62,62,835,310,955,642,723,429,838,722,436,574,619,145,145,148,148,148,339,408,922,619,940,(...TRUNCATED)
[[696,321,321,753,224,976,596,642,956,429,838,536,436,496,619,496,496,496,496,237,131,491,875,619,94(...TRUNCATED)
[[1001,875,875,1001,967,293,58,642,987,429,838,124,436,125,125,496,549,496,496,237,583,1010,344,549,(...TRUNCATED)
[[974,182,20,987,815,862,681,642,646,429,727,412,436,496,549,229,549,496,496,907,900,457,583,619,940(...TRUNCATED)
[[147,596,571,322,147,560,58,322,509,529,337,245,266,768,692,882,721,768,689,882,868,1018,605,295,26(...TRUNCATED)
[[310,957,274,875,310,164,70,642,273,429,838,1,237,496,619,496,496,145,496,260,900,157,164,619,229,7(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"in the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"in the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"and the context of a computer-aided recognition system describe the differences between facial reco(...TRUNCATED)
"In the context of a computer-aided recreational system, describe the differences between facial rec(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"in the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"in the context of a computer-aided recognition system, described the differences between facial rec(...TRUNCATED)
"in the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"in the context of a computer-aided recognition system, described the differences between facial rec(...TRUNCATED)
"in the context of a computer-aided recognition system. Describe the differences between facial reco(...TRUNCATED)
"Facial recognition and fingerprint recognition are two commonly used biometric recognition techniqu(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
"In the context of a computer-aided recognition system, describe the differences between facial reco(...TRUNCATED)
[[865,121,62,62,103,843,721,689,266,926,868,651,687,255,636,368,692,701,813,724,780,408,408,408,876,(...TRUNCATED)
[[73,192,73,565,499,492,266,689,266,926,868,69,687,255,636,368,622,701,813,370,370,73,879,275,73,785(...TRUNCATED)
[[192,499,192,192,499,843,266,689,266,926,868,1018,431,1018,642,531,622,701,782,666,73,1022,192,740,(...TRUNCATED)
[[372,972,627,372,872,801,266,689,419,926,573,1018,681,1018,636,531,622,701,765,192,275,187,814,541,(...TRUNCATED)
[[99,850,836,850,951,850,721,361,322,489,322,778,646,531,431,322,985,81,150,132,815,372,974,814,984,(...TRUNCATED)
[[203,182,722,182,239,428,721,965,882,69,722,182,636,182,925,368,962,701,929,764,846,846,937,233,937(...TRUNCATED)
Name one disadvantage of online shopping
Name one disadvantage of online shopping.
Name one disadvantage of online shopping.
Name one disadvantage of online shopping.
I love you all, I'll be in your name.
looking for forever already something real
Name one disadvantage of online shopping.
Name one disadvantage of online shopping.
name one disadvantage of online shopping
I know you gotta be thirsty in your name.
We're looking for forever, already something real for the deep down
name one disadvantage of online shopping
Name one disadvantage of online shopping.
name one disadvantage of online shopping
I know you got all these girls saying your name
looking for forever or at least something real from the deep down
"One disadvantage of online shopping is the risk of fraud and scams. It is possible to come across f(...TRUNCATED)
Name one disadvantage of online shopping.
Name one disadvantage of online shopping.
Name One Disadvantage of Online Shopping
[[62,408,62,62,408,957,86,143,672,955,813,1023,788,580,801,492,35,906,533,872,872,368,502,890,872,36(...TRUNCATED)
[[999,73,629,370,370,380,143,143,672,982,765,603,580,580,502,502,35,916,533,379,723,847,303,35,137,3(...TRUNCATED)
[[777,325,293,457,696,740,224,368,303,303,748,802,916,239,489,226,788,916,813,586,672,368,80,953,872(...TRUNCATED)
[[274,957,157,875,274,783,530,143,681,974,813,1023,916,685,972,226,540,239,611,958,33,368,944,969,38(...TRUNCATED)
[[614,54,7,607,13,711,109,511,480,758,657,141,801,580,580,189,951,657,706,504,745,806,801,726,908,82(...TRUNCATED)
[[309,99,403,993,811,307,143,266,401,667,244,379,502,226,729,888,803,854,955,446,465,164,740,341,329(...TRUNCATED)
Name one difference between a GPT-3 and traditional language model
Name 1 difference between a GPT-3 and traditional language model.
Name one difference between a GP T3 and traditional language model.
The main one difference between a GPP 3 and a traditional language model
I'm not in a different spot. I think you can do this now.
I'm not a soldier, I'm a scientist
Name one difference between a GPT-3 and traditional language model.
Name one difference between a GPT-3 and traditional language model.
Main one difference between a GPT-3 and traditional language models
I'm different. I keep thinking that I should get some money from the boss.
I'm watching studio and I feel like a fire
Name one difference between a GPT-3 and traditional language model.
Name one difference between a GPT-3 and traditional language model.
The main one difference between the GPT-3 and traditional language model
I'm not even gonna get friends with you. I'm just gonna keep you in my mind and just talk to you.
サムライ戦争リアル トラフサンカス
"A key difference between GPT-3 and traditional language models is the size and training capacity of(...TRUNCATED)
Name one difference between a GPT-3 and traditional language model.
Name one difference between a GPT-3 and traditional language model.
Name one difference between a GPT-3 and traditional language model.
[[121,408,408,62,875,875,687,328,255,605,687,312,960,825,407,489,534,465,489,894,407,465,489,991,955(...TRUNCATED)
[[876,63,368,103,731,672,642,868,255,605,636,825,960,603,407,489,854,167,842,727,407,465,80,969,955,(...TRUNCATED)
[[303,731,731,731,379,872,642,322,776,926,642,312,822,882,407,642,800,167,489,894,407,167,489,822,37(...TRUNCATED)
[[511,511,511,541,511,511,431,266,509,572,906,322,960,825,419,572,715,814,842,727,536,167,842,59,273(...TRUNCATED)
[[236,231,654,830,593,715,341,485,4,560,654,322,620,644,401,660,790,951,361,854,593,382,51,951,951,7(...TRUNCATED)
[[498,715,511,308,543,480,493,729,401,558,297,600,401,435,55,401,787,654,842,715,759,859,854,817,842(...TRUNCATED)
Output a list of items needed to have a picnic.
Outflow lists of items needed to have a picnic.
output list of items needed to have a picnic.
output list of items needed to have a picnic.
Outflow lists of items needed to have a picnic.
Outplay lists of items needed to have a picnic.
I'll put a list of items needed to have a picnic.
I'll put a list of items needed to have a picnic.
I'll put a list of items needed to have a picnic.
output list of items needed to have a picnic.
Our playlist of items needed to have a picnic.
Output list of items needed to have a picnic
Output list of items needed to have a picnic
Output a list of items needed to have a picnic
Output list of items needed to have the picnic
Output a list of items needed to have the picnic
"Here is a list of items you may need for a picnic:\n\n1. Picnic blanket or tablecloth\n2. Basket or(...TRUNCATED)
output list of items needed to have a picnic.
I'll put a list of items needed to have a picnic.
Output a list of items needed to have a picnic.
[[62,62,62,62,408,395,835,461,869,233,213,997,478,213,213,936,112,879,738,738,408,798,176,499,176,49(...TRUNCATED)
[[860,370,783,753,30,293,323,461,869,233,128,997,478,128,213,936,112,879,347,323,323,843,798,409,488(...TRUNCATED)
[[925,791,1001,323,783,598,598,843,869,233,128,997,478,128,213,936,112,598,598,598,931,495,237,611,1(...TRUNCATED)
[[931,191,931,858,868,931,344,858,869,233,324,997,478,213,203,467,112,598,80,530,530,563,765,540,436(...TRUNCATED)
[[339,339,25,339,537,395,395,677,869,358,213,997,213,213,213,936,112,879,339,25,463,537,176,461,176,(...TRUNCATED)
[[784,108,784,259,367,12,564,460,535,322,844,956,948,376,476,928,197,311,79,928,746,191,1020,939,57,(...TRUNCATED)
Can you create a story that ends with the sentence "The river wound its way through the forest"?
Can you create a story that ends with the sentence, the river loomed its way through the forest?
It can create a story that ends with the sentence the river wound its way through the forest.
Can you create a story that ends with a sentence that never went its way through the forest?
Can you create a story that ends with the sentence, and never will this wait through the forest?
You create a story that ends with a sentence never in this world through words
Can you create a story that ends with a sentence or ever wound its way through the forest?
Can you create a story that ends with the sentence of everyone its way through the forest?
Can you create a story that ends with a sentence that revel in its way through the forest?
Can you create a story that ends with the sentence of everyone's way through the forest?
I can create a story that ends with a sentence that never ends with a story feeling worse
Can you create a story that ends with the sentence the river wound its way through the forest?
Can you create a story that ends with the sentence, the river wound its way through the forest?
Can you create a story that ends with a sentence that reverberates its way through the forest?
Can you create a story that ends with the sentence, A river will be swayed through the forest,
I can't create a story that ends with a sentence that never ends well through the words.
"The river wound its way through the forest, cascading over rocks and tumbling through rapids as it (...TRUNCATED)
Can you create a story that ends with the sentence of River Wound its way through the forest?
Can you create a story that ends with the sentence The river wound its way through the forest?
Can you create a story that ends with the sentence of Ever wound its way through the forest?
[[865,121,121,835,237,496,148,237,759,822,561,923,977,770,328,311,776,822,559,1008,935,73,73,395,461(...TRUNCATED)
[[73,276,604,731,940,496,488,940,759,822,759,923,311,770,328,311,776,822,559,979,537,73,499,274,461,(...TRUNCATED)
[[777,380,783,740,731,496,628,940,759,328,770,328,977,770,328,311,800,603,759,511,461,461,499,499,46(...TRUNCATED)
[[433,103,537,276,237,496,148,237,759,822,561,456,977,770,328,857,776,822,559,979,676,499,783,819,46(...TRUNCATED)
[[108,193,637,132,246,802,194,729,759,960,850,200,489,142,462,142,142,960,361,511,461,461,461,708,26(...TRUNCATED)
[[659,891,401,562,401,41,659,248,660,243,655,721,960,536,324,939,790,956,485,132,814,233,31,849,1007(...TRUNCATED)
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Dataset Card for "MUSAN-music_unit"

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5,135