Towards end-2-end learning for predicting behavior codes from spoken utterances in psychotherapy conversations

ACL 2020 Karan SinglaZhuohao ChenDavid AtkinsShrikanth Narayanan

Spoken language understanding tasks usually rely on pipelines involving complex processing blocks such as voice activity detection, speaker diarization and Automatic speech recognition (ASR). We propose a novel framework for predicting utterance level labels directly from speech features, thus removing the dependency on first generating transcripts, and transcription free behavioral coding... (read more)

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