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 paper "Domain Specific Wav2vec 2.0 Fine-tuning For The SE&R 2022 Challenge"
Code for the winning solution in the SE&R 2022 Challenge - SER track.
354-Hours-Dari-Spontaneous-Dialogue-Smartphone-speech-dataset
103-Hours-Indonesian-Spontaneous-Dialogue-Smartphone-Speech-Dataset
175-Hours-Thai-Spontaneous-Dialogue-Smartphone-speech-dataset
99-Hours-Pashto-Spontaneous-Dialogue-Smartphone-speech-dataset
202-Hours-German-Gaming-Real-world-Casual-Conversation-and-Monologue-speech-dataset
147-Hours-Filipino-Spontaneous-Dialogue-Telephony-speech-dataset
Vietnamese-Spontaneous-Dialogue-Telephony-speech-dataset
34-Hours-Hindi-Child-Spontaneous-Speech-Data
500-Hours-Brazilian-Portuguese-Spontaneous-Speech-Data
58-Hours-European-Portuguese-Child-s-Spontaneous-Speech-Data-Nexdata
501-Hours-Indonesian-Spontaneous-Speech-Data
128-Hours-Australian-English-Child-Spontaneous-Speech-Data
149-Hours-British-English-Child-Spontaneous-Speech-Data
145-Hours-Spanish-Child-Spontaneous-Speech-Data
711-Hours-Vietnamese-Spontaneous-Speech-Data
176-Hours-Tibetan-Spontaneous-Speech-Data
557-Hours-Kazakh-Spontaneous-Speech-Data
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