Search Results for author: Yatharth Saraf

Found 18 papers, 1 papers with code

Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions

no code implementations18 Nov 2021 Chunxi Liu, Michael Picheny, Leda Sari, Pooja Chitkara, Alex Xiao, Xiaohui Zhang, Mark Chou, Andres Alvarado, Caner Hazirbas, Yatharth Saraf

This paper presents initial Speech Recognition results on "Casual Conversations" -- a publicly released 846 hour corpus designed to help researchers evaluate their computer vision and audio models for accuracy across a diverse set of metadata, including age, gender, and skin tone.

Automatic Speech Recognition Fairness

Scaling ASR Improves Zero and Few Shot Learning

no code implementations10 Nov 2021 Alex Xiao, Weiyi Zheng, Gil Keren, Duc Le, Frank Zhang, Christian Fuegen, Ozlem Kalinli, Yatharth Saraf, Abdelrahman Mohamed

With 4. 5 million hours of English speech from 10 different sources across 120 countries and models of up to 10 billion parameters, we explore the frontiers of scale for automatic speech recognition.

Automatic Speech Recognition Few-Shot Learning

Conformer-Based Self-Supervised Learning for Non-Speech Audio Tasks

no code implementations14 Oct 2021 Sangeeta Srivastava, Yun Wang, Andros Tjandra, Anurag Kumar, Chunxi Liu, Kritika Singh, Yatharth Saraf

While self-supervised speech representation learning has been popular in the speech research community, very few works have comprehensively analyzed audio representation learning for non-speech audio tasks.

Audio Classification Representation Learning +1

Kaizen: Continuously improving teacher using Exponential Moving Average for semi-supervised speech recognition

no code implementations14 Jun 2021 Vimal Manohar, Tatiana Likhomanenko, Qiantong Xu, Wei-Ning Hsu, Ronan Collobert, Yatharth Saraf, Geoffrey Zweig, Abdelrahman Mohamed

In this paper, we introduce the Kaizen framework that uses a continuously improving teacher to generate pseudo-labels for semi-supervised speech recognition (ASR).

Frame Speech Recognition

A Multi-View Approach To Audio-Visual Speaker Verification

no code implementations11 Feb 2021 Leda Sari, Kritika Singh, Jiatong Zhou, Lorenzo Torresani, Nayan Singhal, Yatharth Saraf

Although speaker verification has conventionally been an audio-only task, some practical applications provide both audio and visual streams of input.

Speaker Verification

Benchmarking LF-MMI, CTC and RNN-T Criteria for Streaming ASR

no code implementations9 Nov 2020 Xiaohui Zhang, Frank Zhang, Chunxi Liu, Kjell Schubert, Julian Chan, Pradyot Prakash, Jun Liu, Ching-Feng Yeh, Fuchun Peng, Yatharth Saraf, Geoffrey Zweig

In this work, to measure the accuracy and efficiency for a latency-controlled streaming automatic speech recognition (ASR) application, we perform comprehensive evaluations on three popular training criteria: LF-MMI, CTC and RNN-T.

Automatic Speech Recognition

Improving RNN Transducer Based ASR with Auxiliary Tasks

no code implementations5 Nov 2020 Chunxi Liu, Frank Zhang, Duc Le, Suyoun Kim, Yatharth Saraf, Geoffrey Zweig

End-to-end automatic speech recognition (ASR) models with a single neural network have recently demonstrated state-of-the-art results compared to conventional hybrid speech recognizers.

Automatic Speech Recognition

Contextual RNN-T For Open Domain ASR

no code implementations4 Jun 2020 Mahaveer Jain, Gil Keren, Jay Mahadeokar, Geoffrey Zweig, Florian Metze, Yatharth Saraf

By using an attention model and a biasing model to leverage the contextual metadata that accompanies a video, we observe a relative improvement of about 16% in Word Error Rate on Named Entities (WER-NE) for videos with related metadata.

Automatic Speech Recognition

Faster, Simpler and More Accurate Hybrid ASR Systems Using Wordpieces

no code implementations19 May 2020 Frank Zhang, Yongqiang Wang, Xiaohui Zhang, Chunxi Liu, Yatharth Saraf, Geoffrey Zweig

In this work, we first show that on the widely used LibriSpeech benchmark, our transformer-based context-dependent connectionist temporal classification (CTC) system produces state-of-the-art results.

Frame Speech Recognition

Large scale weakly and semi-supervised learning for low-resource video ASR

no code implementations16 May 2020 Kritika Singh, Vimal Manohar, Alex Xiao, Sergey Edunov, Ross Girshick, Vitaliy Liptchinsky, Christian Fuegen, Yatharth Saraf, Geoffrey Zweig, Abdel-rahman Mohamed

Many semi- and weakly-supervised approaches have been investigated for overcoming the labeling cost of building high quality speech recognition systems.

Frame Speech Recognition

Multilingual Graphemic Hybrid ASR with Massive Data Augmentation

no code implementations LREC 2020 Chunxi Liu, Qiaochu Zhang, Xiaohui Zhang, Kritika Singh, Yatharth Saraf, Geoffrey Zweig

Towards developing high-performing ASR for low-resource languages, approaches to address the lack of resources are to make use of data from multiple languages, and to augment the training data by creating acoustic variations.

Data Augmentation

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