Finite-Time Adaptive Fuzzy Tracking Control for Nonlinear State Constrained Pure-Feedback Systems

no code implementations • 23 Oct 2023 • Ju Wu, Tong Wang, Min Ma

This paper investigates the finite-time adaptive fuzzy tracking control problem for a class of pure-feedback system with full-state constraints.

Multimodal Modeling For Spoken Language Identification

no code implementations • 19 Sep 2023 • Shikhar Bharadwaj, Min Ma, Shikhar Vashishth, Ankur Bapna, Sriram Ganapathy, Vera Axelrod, Siddharth Dalmia, Wei Han, Yu Zhang, Daan van Esch, Sandy Ritchie, Partha Talukdar, Jason Riesa

Spoken language identification refers to the task of automatically predicting the spoken language in a given utterance.

Language Identification Spoken language identification

MASR: Multi-label Aware Speech Representation

no code implementations • 20 Jul 2023 • Anjali Raj, Shikhar Bharadwaj, Sriram Ganapathy, Min Ma, Shikhar Vashishth

In the recent years, speech representation learning is constructed primarily as a self-supervised learning (SSL) task, using the raw audio signal alone, while ignoring the side-information that is often available for a given speech recording.

Emotion Recognition Language Identification +4

Label Aware Speech Representation Learning For Language Identification

no code implementations • 7 Jun 2023 • Shikhar Vashishth, Shikhar Bharadwaj, Sriram Ganapathy, Ankur Bapna, Min Ma, Wei Han, Vera Axelrod, Partha Talukdar

In this paper, we propose a novel framework of combining self-supervised representation learning with the language label information for the pre-training task.

Language Identification Missing Labels +3

XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages

1 code implementation • 19 May 2023 • Sebastian Ruder, Jonathan H. Clark, Alexander Gutkin, Mihir Kale, Min Ma, Massimo Nicosia, Shruti Rijhwani, Parker Riley, Jean-Michel A. Sarr, Xinyi Wang, John Wieting, Nitish Gupta, Anna Katanova, Christo Kirov, Dana L. Dickinson, Brian Roark, Bidisha Samanta, Connie Tao, David I. Adelani, Vera Axelrod, Isaac Caswell, Colin Cherry, Dan Garrette, Reeve Ingle, Melvin Johnson, Dmitry Panteleev, Partha Talukdar

We evaluate commonly used models on the benchmark.

In-Context Learning Multilingual NLP +3

FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech

1 code implementation • 25 May 2022 • Alexis Conneau, Min Ma, Simran Khanuja, Yu Zhang, Vera Axelrod, Siddharth Dalmia, Jason Riesa, Clara Rivera, Ankur Bapna

We introduce FLEURS, the Few-shot Learning Evaluation of Universal Representations of Speech benchmark.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +6

XTREME-S: Evaluating Cross-lingual Speech Representations

no code implementations • 21 Mar 2022 • Alexis Conneau, Ankur Bapna, Yu Zhang, Min Ma, Patrick von Platen, Anton Lozhkov, Colin Cherry, Ye Jia, Clara Rivera, Mihir Kale, Daan van Esch, Vera Axelrod, Simran Khanuja, Jonathan H. Clark, Orhan Firat, Michael Auli, Sebastian Ruder, Jason Riesa, Melvin Johnson

Covering 102 languages from 10+ language families, 3 different domains and 4 task families, XTREME-S aims to simplify multilingual speech representation evaluation, as well as catalyze research in "universal" speech representation learning.

Representation Learning Retrieval +4

BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition

no code implementations • 27 Sep 2021 • Yu Zhang, Daniel S. Park, Wei Han, James Qin, Anmol Gulati, Joel Shor, Aren Jansen, Yuanzhong Xu, Yanping Huang, Shibo Wang, Zongwei Zhou, Bo Li, Min Ma, William Chan, Jiahui Yu, Yongqiang Wang, Liangliang Cao, Khe Chai Sim, Bhuvana Ramabhadran, Tara N. Sainath, Françoise Beaufays, Zhifeng Chen, Quoc V. Le, Chung-Cheng Chiu, Ruoming Pang, Yonghui Wu

We summarize the results of a host of efforts using giant automatic speech recognition (ASR) models pre-trained using large, diverse unlabeled datasets containing approximately a million hours of audio.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Scaling End-to-End Models for Large-Scale Multilingual ASR

no code implementations • 30 Apr 2021 • Bo Li, Ruoming Pang, Tara N. Sainath, Anmol Gulati, Yu Zhang, James Qin, Parisa Haghani, W. Ronny Huang, Min Ma, Junwen Bai

Building ASR models across many languages is a challenging multi-task learning problem due to large variations and heavily unbalanced data.

Multi-Task Learning

Improving Streaming Automatic Speech Recognition With Non-Streaming Model Distillation On Unsupervised Data

no code implementations • 22 Oct 2020 • Thibault Doutre, Wei Han, Min Ma, Zhiyun Lu, Chung-Cheng Chiu, Ruoming Pang, Arun Narayanan, Ananya Misra, Yu Zhang, Liangliang Cao

We propose a novel and effective learning method by leveraging a non-streaming ASR model as a teacher to generate transcripts on an arbitrarily large data set, which is then used to distill knowledge into streaming ASR models.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

CUNY Systems for the Query-by-Example Search on Speech Task at MediaEval 2015

no code implementations • MediaEval 2015 Workshop 2015 • Min Ma, Andrew Rosenberg

This paper describes two query-by-example systems developed by Speech Lab, Queens College (CUNY).

Keyword Spotting