Search Results for author:
Found 13 papers, 1 papers with code
Zipper: A Multi-Tower Decoder Architecture for Fusing Modalities
In cross-modal tasks such as text-to-speech generation (TTS) where the output modality is speech, we show that using a pre-trained speech backbone results in superior performance to the baseline.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Robust Preference Optimization through Reward Model Distillation
Moreover, to account for uncertainty in the reward model we are distilling from, we optimize against a family of reward models that, as a whole, is likely to include at least one reasonable proxy for the preference distribution.
AudioPaLM: A Large Language Model That Can Speak and Listen
AudioPaLM inherits the capability to preserve paralinguistic information such as speaker identity and intonation from AudioLM and the linguistic knowledge present only in text large language models such as PaLM-2.
MultiTurnCleanup: A Benchmark for Multi-Turn Spoken Conversational Transcript Cleanup
Current disfluency detection models focus on individual utterances each from a single speaker.
Teaching BERT to Wait: Balancing Accuracy and Latency for Streaming Disfluency Detection
In modern interactive speech-based systems, speech is consumed and transcribed incrementally prior to having disfluencies removed.
Residual Adapters for Parameter-Efficient ASR Adaptation to Atypical and Accented Speech
We demonstrate this on two speech adaptation tasks (atypical and accented speech) and for two state-of-the-art ASR architectures.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Disfluency Detection with Unlabeled Data and Small BERT Models
However, little exploration has been done in improving the size and inference time of the model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Representations for Question Answering from Documents with Tables and Text
Tables in Web documents are pervasive and can be directly used to answer many of the queries searched on the Web, motivating their integration in question answering.
Giving Attention to the Unexpected: Using Prosody Innovations in Disfluency Detection
Disfluencies in spontaneous speech are known to be associated with prosodic disruptions.
Disfluencies and Human Speech Transcription Errors
This paper explores contexts associated with errors in transcrip-tion of spontaneous speech, shedding light on human perceptionof disfluencies and other conversational speech phenomena.
Robust cross-domain disfluency detection with pattern match networks
In this paper we introduce a novel pattern match neural network architecture that uses neighbor similarity scores as features, eliminating the need for feature engineering in a disfluency detection task.
Conversation Modeling on Reddit using a Graph-Structured LSTM
This paper presents a novel approach for modeling threaded discussions on social media using a graph-structured bidirectional LSTM which represents both hierarchical and temporal conversation structure.
Disfluency Detection using a Bidirectional LSTM
We introduce a new approach for disfluency detection using a Bidirectional Long-Short Term Memory neural network (BLSTM).
