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Found 6 papers, 1 papers with code
SpeechVerse: A Large-scale Generalizable Audio Language Model
The models are instruction finetuned using continuous latent representations extracted from the speech foundation model to achieve optimal zero-shot performance on a diverse range of speech processing tasks using natural language instructions.
Generalized zero-shot audio-to-intent classification
Our multimodal training approach improves the accuracy of zero-shot intent classification on unseen intents of SLURP by 2. 75% and 18. 2% for the SLURP and internal goal-oriented dialog datasets, respectively, compared to audio-only training.
End-to-End Single-Channel Speaker-Turn Aware Conversational Speech Translation
Conventional speech-to-text translation (ST) systems are trained on single-speaker utterances, and they may not generalize to real-life scenarios where the audio contains conversations by multiple speakers.
Speaker Diarization of Scripted Audiovisual Content
The media localization industry usually requires a verbatim script of the final film or TV production in order to create subtitles or dubbing scripts in a foreign language.
Lexical Speaker Error Correction: Leveraging Language Models for Speaker Diarization Error Correction
Speaker diarization (SD) is typically used with an automatic speech recognition (ASR) system to ascribe speaker labels to recognized words.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Directed Speech Separation for Automatic Speech Recognition of Long Form Conversational Speech
Also, most of these models are trained with synthetic mixtures and do not generalize to real conversational data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
