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1
Exploiting a Zoo of Checkpoints for Unseen Tasks ...
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2
First DIHARD Challenge -- System Submissions and Scores ...
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3
First DIHARD Challenge -- System Submissions and Scores ...
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4
Decoupling recognition and transcription in Mandarin ASR ...
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5
Automatic recognition of suprasegmentals in speech ...
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6
The Role of Phonetic Units in Speech Emotion Recognition ...
Abstract: We propose a method for emotion recognition through emotiondependent speech recognition using Wav2vec 2.0. Our method achieved a significant improvement over most previously reported results on IEMOCAP, a benchmark emotion dataset. Different types of phonetic units are employed and compared in terms of accuracy and robustness of emotion recognition within and across datasets and languages. Models of phonemes, broad phonetic classes, and syllables all significantly outperform the utterance model, demonstrating that phonetic units are helpful and should be incorporated in speech emotion recognition. The best performance is from using broad phonetic classes. Further research is needed to investigate the optimal set of broad phonetic classes for the task of emotion recognition. Finally, we found that Wav2vec 2.0 can be fine-tuned to recognize coarser-grained or larger phonetic units than phonemes, such as broad phonetic classes and syllables. ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2108.01132
https://dx.doi.org/10.48550/arxiv.2108.01132
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7
Data Collection vs. Knowledge Graph Completion: What is Needed to Improve Coverage? ...
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8
The Future of Computational Linguistics: On Beyond Alchemy
In: Front Artif Intell (2021)
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9
On Finite State Parsing
In: University of Massachusetts Occasional Papers in Linguistics (2020)
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10
The Second DIHARD Diarization Challenge: Dataset, task, and baselines ...
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11
ENHANCEMENT AND ANALYSIS OF CONVERSATIONAL SPEECH: JSALT 2017
Profant, Jan; Tsao, Yu; Du, Jun. - : IEEE, 2018
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12
Approximate inference: A sampling based modeling technique to capture complex dependencies in a language model
In: Speech communication. - Amsterdam [u.a.] : Elsevier 55 (2013) 1, 162-177
OLC Linguistik
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13
Approximate inference: a sampling based modeling technique to capture complex dependencies in a language model
In: Speech communication. - Amsterdam [u.a.] : Elsevier 55 (2013) 1, 162-177
BLLDB
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14
A Summary of the 2012 JHU CLSP workshop on zero resource speech technologies and models of early language acquisition
Jansen, Aren; Dupoux, Emmanuel; Seltzer, Mike. - : Piscataway, NJ : IEEE, 2013
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15
A summary of the 2012 JHU CLSP workshop on zero resource speech technologies and models of early language acquisition ...
Jansen, Aren; Dupoux, Emmanuel; Goldwater, Sharon. - : Carnegie Mellon University, 2013
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16
A summary of the 2012 JHU CLSP workshop on zero resource speech technologies and models of early language acquisition ...
Jansen, Aren; Dupoux, Emmanuel; Goldwater, Sharon. - : Carnegie Mellon University, 2013
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17
Estimation problems in speech and natural language
Bhat, Suma P.. - 2010
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18
Contextual text mining
Mei, Qiaozhu. - 2009
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19
Approximate Lexicography and Web Search
In: International Journal of Lexicography 21 (2008) 3, 325-336
IDS OBELEX meta
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20
Approximate lexicography and Web search
In: International journal of lexicography. - Oxford : Oxford Univ. Press 21 (2008) 3, 325-336
BLLDB
OLC Linguistik
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