43 citations · 56 across the 8 of their papers we have counts for
12 papers
AudioPaLM: A Large Language Model That Can Speak and Listen
Paul K. Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen +27
We introduce AudioPaLM, a large language model for speech understanding and generation. AudioPaLM fuses text-based and speech-based language models, PaLM-2 [Anil et al., 2023] and…
MultiTurnCleanup: A Benchmark for Multi-Turn Spoken Conversational Transcript Cleanup
Hua Shen, Vicky Zayats, Johann C. Rocholl +2
Current disfluency detection models focus on individual utterances each from a single speaker. However, numerous discontinuity phenomena in spoken conversational transcripts occur…
Teaching BERT to Wait: Balancing Accuracy and Latency for Streaming Disfluency Detection
Angelica Chen, Vicky Zayats, Daniel D. Walker +1
In modern interactive speech-based systems, speech is consumed and transcribed incrementally prior to having disfluencies removed. This post-processing step is crucial for producin…
Residual Adapters for Parameter-Efficient ASR Adaptation to Atypical and Accented Speech
Katrin Tomanek, Vicky Zayats, Dirk Padfield +2
Automatic Speech Recognition (ASR) systems are often optimized to work best for speakers with canonical speech patterns. Unfortunately, these systems perform poorly when tested on…
Disfluency Detection with Unlabeled Data and Small BERT Models
Johann C. Rocholl, Vicky Zayats, Daniel D. Walker +3
Disfluency detection models now approach high accuracy on English text. However, little exploration has been done in improving the size and inference time of the model. At the same…
Representations for Question Answering from Documents with Tables and Text
Vicky Zayats, Kristina Toutanova, Mari Ostendorf
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. Very often inf…
Disfluencies and Human Speech Transcription Errors
Vicky Zayats, Trang Tran, Richard Wright +2
This paper explores contexts associated with errors in transcrip-tion of spontaneous speech, shedding light on human perceptionof disfluencies and other conversational speech pheno…
Giving Attention to the Unexpected: Using Prosody Innovations in Disfluency Detection
Vicky Zayats, Mari Ostendorf
Disfluencies in spontaneous speech are known to be associated with prosodic disruptions. However, most algorithms for disfluency detection use only word transcripts. Integrating pr…
Robust cross-domain disfluency detection with pattern match networks
Vicky Zayats, Mari Ostendorf
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 dis…
Conversation Modeling on Reddit using a Graph-Structured LSTM
Vicky Zayats, Mari Ostendorf
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 c…
Disfluency Detection using a Bidirectional LSTM
Vicky Zayats, Mari Ostendorf, Hannaneh Hajishirzi
We introduce a new approach for disfluency detection using a Bidirectional Long-Short Term Memory neural network (BLSTM). In addition to the word sequence, the model takes as input…
Talking to the crowd: What do people react to in online discussions?
Aaron Jaech, Victoria Zayats, Hao Fang +2
This paper addresses the question of how language use affects community reaction to comments in online discussion forums, and the relative importance of the message vs. the messeng…