A new metric for evaluating end-to-end speech recognition and disfluency removal systems
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Updated
Mar 7, 2021 - Python
A new metric for evaluating end-to-end speech recognition and disfluency removal systems
Code for the winning solution in the SE&R 2022 Challenge - SER track.
Code for the paper "Domain Specific Wav2vec 2.0 Fine-tuning For The SE&R 2022 Challenge"
34-Hours-Hindi-Child-Spontaneous-Speech-Data
302-Person-Hindi-and-English-Bilingual-Spontaneous-Monologue-smartphone-speech-dataset
176-Hours-Tibetan-Spontaneous-Speech-Data
354-Hours-Dari-Spontaneous-Dialogue-Smartphone-speech-dataset
58-Hours-European-Portuguese-Child-s-Spontaneous-Speech-Data-Nexdata
149-Hours-British-English-Child-Spontaneous-Speech-Data
202-Hours-German-Gaming-Real-world-Casual-Conversation-and-Monologue-speech-dataset
145-Hours-Spanish-Child-Spontaneous-Speech-Data
711-Hours-Vietnamese-Spontaneous-Speech-Data
103-Hours-Indonesian-Spontaneous-Dialogue-Smartphone-Speech-Dataset
175-Hours-Thai-Spontaneous-Dialogue-Smartphone-speech-dataset
Vietnamese-Spontaneous-Dialogue-Telephony-speech-dataset
557-Hours-Kazakh-Spontaneous-Speech-Data
99-Hours-Pashto-Spontaneous-Dialogue-Smartphone-speech-dataset
97-Hours-Brazilian-Portuguese-Child-Spontaneous-Speech-Data
128-Hours-Australian-English-Child-Spontaneous-Speech-Data
147-Hours-Filipino-Spontaneous-Dialogue-Telephony-speech-dataset
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