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    Home»AI Tools»Google at Interspeech 2023 – Google Research Blog
    AI Tools

    Google at Interspeech 2023 – Google Research Blog

    By August 21, 2023No Comments4 Mins Read
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    Posted by Catherine Armato, Program Manager, Google

    This week, the 24th Annual Conference of the International Speech Communication Association (INTERSPEECH 2023) is being held in Dublin, Ireland, representing one of the world’s most extensive conferences on research and technology of spoken language understanding and processing. Experts in speech-related research fields gather to take part in oral presentations and poster sessions and to build collaborations across the globe.

    We are excited to be a Platinum Sponsor of INTERSPEECH 2023, where we will be showcasing more than 20 research publications and supporting a number of workshops and special sessions. We welcome in-person attendees to drop by the Google Research booth to meet our researchers and participate in Q&As and demonstrations of some of our latest speech technologies, which help to improve accessibility and provide convenience in communication for billions of users. In addition, online attendees are encouraged to visit our virtual booth in Topia where you can get up-to-date information on research and opportunities at Google. Visit the @GoogleAI Twitter account to find out about Google booth activities (e.g., demos and Q&A sessions). You can also learn more about the Google research being presented at INTERSPEECH 2023 below (Google affiliations in bold).

    Board and Organizing Committee

    ISCA Board, Technical Committee Chair: Bhuvana Ramabhadran

    Area Chairs include:
        Analysis of Speech and Audio Signals: Richard Rose
        Speech Synthesis and Spoken Language Generation: Rob Clark
        Special Areas: Tara Sainath

    Satellite events

    Keynote talk – ISCA Medalist

    Survey Talk

    Speech Compression in the AI Era
    Speaker: Jan Skoglund

    Special session papers

    Cascaded Encoders for Fine-Tuning ASR Models on Overlapped Speech
    Richard Rose, Oscar Chang, Olivier Siohan

    TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition
    Hakan Erdogan, Scott Wisdom, Xuankai Chang*, Zalán Borsos, Marco Tagliasacchi, Neil Zeghidour, John R. Hershey

    Papers

    DeePMOS: Deep Posterior Mean-Opinion-Score of Speech
    Xinyu Liang, Fredrik Cumlin, Christian Schüldt, Saikat Chatterjee

    O-1: Self-Training with Oracle and 1-Best Hypothesis
    Murali Karthick Baskar, Andrew Rosenberg, Bhuvana Ramabhadran, Kartik Audhkhasi

    Re-investigating the Efficient Transfer Learning of Speech Foundation Model Using Feature Fusion Methods
    Zhouyuan Huo, Khe Chai Sim, Dongseong Hwang, Tsendsuren Munkhdalai, Tara N. Sainath, Pedro Moreno

    MOS vs. AB: Evaluating Text-to-Speech Systems Reliably Using Clustered Standard Errors
    Joshua Camp, Tom Kenter, Lev Finkelstein, Rob Clark

    LanSER: Language-Model Supported Speech Emotion Recognition
    Taesik Gong, Josh Belanich, Krishna Somandepalli, Arsha Nagrani, Brian Eoff, Brendan Jou

    Modular Domain Adaptation for Conformer-Based Streaming ASR
    Qiujia Li, Bo Li, Dongseong Hwang, Tara N. Sainath, Pedro M. Mengibar

    On Training a Neural Residual Acoustic Echo Suppressor for Improved ASR
    Sankaran Panchapagesan, Turaj Zakizadeh Shabestary, Arun Narayanan

    MD3: The Multi-dialect Dataset of Dialogues
    Jacob Eisenstein, Vinodkumar Prabhakaran, Clara Rivera, Dorottya Demszky, Devyani Sharma

    Dual-Mode NAM: Effective Top-K Context Injection for End-to-End ASR
    Zelin Wu, Tsendsuren Munkhdalai, Pat Rondon, Golan Pundak, Khe Chai Sim, Christopher Li

    Using Text Injection to Improve Recognition of Personal Identifiers in Speech
    Yochai Blau, Rohan Agrawal, Lior Madmony, Gary Wang, Andrew Rosenberg, Zhehuai Chen, Zorik Gekhman, Genady Beryozkin, Parisa Haghani, Bhuvana Ramabhadran

    How to Estimate Model Transferability of Pre-trained Speech Models?
    Zih-Ching Chen, Chao-Han Huck Yang*, Bo Li, Yu Zhang, Nanxin Chen, Shuo-yiin Chang, Rohit Prabhavalkar, Hung-yi Lee, Tara N. Sainath

    Improving Joint Speech-Text Representations Without Alignment
    Cal Peyser, Zhong Meng, Ke Hu, Rohit Prabhavalkar, Andrew Rosenberg, Tara N. Sainath, Michael Picheny, Kyunghyun Cho

    Text Injection for Capitalization and Turn-Taking Prediction in Speech Models
    Shaan Bijwadia, Shuo-yiin Chang, Weiran Wang, Zhong Meng, Hao Zhang, Tara N. Sainath

    Streaming Parrotron for On-Device Speech-to-Speech Conversion
    Oleg Rybakov, Fadi Biadsy, Xia Zhang, Liyang Jiang, Phoenix Meadowlark, Shivani Agrawal

    Semantic Segmentation with Bidirectional Language Models Improves Long-Form ASR
    W. Ronny Huang, Hao Zhang, Shankar Kumar, Shuo-yiin Chang, Tara N. Sainath

    Universal Automatic Phonetic Transcription into the International Phonetic Alphabet
    Chihiro Taguchi, Yusuke Sakai, Parisa Haghani, David Chiang

    Mixture-of-Expert Conformer for Streaming Multilingual ASR
    Ke Hu, Bo Li, Tara N. Sainath, Yu Zhang, Francoise Beaufays

    Real Time Spectrogram Inversion on Mobile Phone
    Oleg Rybakov, Marco Tagliasacchi, Yunpeng Li, Liyang Jiang, Xia Zhang, Fadi Biadsy

    2-Bit Conformer Quantization for Automatic Speech Recognition
    Oleg Rybakov, Phoenix Meadowlark, Shaojin Ding, David Qiu, Jian Li, David Rim, Yanzhang He

    LibriTTS-R: A Restored Multi-speaker Text-to-Speech Corpus
    Yuma Koizumi, Heiga Zen, Shigeki Karita, Yifan Ding, Kohei Yatabe, Nobuyuki Morioka, Michiel Bacchiani, Yu Zhang, Wei Han, Ankur Bapna

    PronScribe: Highly Accurate Multimodal Phonemic Transcription from Speech and Text
    Yang Yu, Matthew Perez*, Ankur Bapna, Fadi Haik, Siamak Tazari, Yu Zhang

    Label Aware Speech Representation Learning for Language Identification
    Shikhar Vashishth, Shikhar Bharadwaj, Sriram Ganapathy, Ankur Bapna, Min Ma, Wei Han, Vera Axelrod, Partha Talukdar


    * Work done while at Google



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