461 citations · 1.7k across the 40 of their papers we have counts for
42 papers
AV-SUPERB: A Multi-Task Evaluation Benchmark for Audio-Visual Representation Models
Yuan Tseng, Layne Berry, Yi-Ting Chen +16
Audio-visual representation learning aims to develop systems with human-like perception by utilizing correlation between auditory and visual information. However, current models of…
Syllable Discovery and Cross-Lingual Generalization in a Visually Grounded, Self-Supervised Speech Model
Puyuan Peng, Shang-Wen Li, Okko Räsänen +2
In this paper, we show that representations capturing syllabic units emerge when training a self-supervised speech model with a visually-grounded training objective. We demonstrate…
ML-SUPERB: Multilingual Speech Universal PERformance Benchmark
Jiatong Shi, Dan Berrebbi, William Chen +8
Speech processing Universal PERformance Benchmark (SUPERB) is a leaderboard to benchmark the performance of Self-Supervised Learning (SSL) models on various speech processing tasks…
SUPERB @ SLT 2022: Challenge on Generalization and Efficiency of Self-Supervised Speech Representation Learning
Tzu-hsun Feng, Annie Dong, Ching-Feng Yeh +11
We present the SUPERB challenge at SLT 2022, which aims at learning self-supervised speech representation for better performance, generalization, and efficiency. The challenge buil…
STOP: A dataset for Spoken Task Oriented Semantic Parsing
Paden Tomasello, Akshat Shrivastava, Daniel Lazar +12
End-to-end spoken language understanding (SLU) predicts intent directly from audio using a single model. It promises to improve the performance of assistant systems by leveraging a…
Intelligent Omni-Surfaces (IOSs) for the MIMO Broadcast Channel
Abdelhamed Mohamed, Nemanja Stefan Perović, Marco Di Renzo
In this paper, we consider intelligent omni-surfaces (IOSs), which are capable of simultaneously reflecting and refracting electromagnetic waves. We focus our attention on the mult…
A Proposed Sub-optimal Power Allocation using Simulated Annealing in Cognitive Radio Networks
Abdelhamed Mohamed, Mona Shokair, Mohamed Elkordy +1
Due to the rapid demand for wireless services and the increase in the wireless device count, there is a lack of available spectrum bands which constrain the further development of…
DP-Parse: Finding Word Boundaries from Raw Speech with an Instance Lexicon
Robin Algayres, Tristan Ricoul, Julien Karadayi +5
Finding word boundaries in continuous speech is challenging as there is little or no equivalent of a 'space' delimiter between words. Popular Bayesian non-parametric models for tex…
LegoNN: Building Modular Encoder-Decoder Models
Siddharth Dalmia, Dmytro Okhonko, Mike Lewis +5
State-of-the-art encoder-decoder models (e.g. for machine translation (MT) or automatic speech recognition (ASR)) are constructed and trained end-to-end as an atomic unit. No compo…
Self-Supervised Speech Representation Learning: A Review
Abdelrahman Mohamed, Hung-yi Lee, Lasse Borgholt +9
Although supervised deep learning has revolutionized speech and audio processing, it has necessitated the building of specialist models for individual tasks and application scenari…
SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities
Hsiang-Sheng Tsai, Heng-Jui Chang, Wen-Chin Huang +14
Transfer learning has proven to be crucial in advancing the state of speech and natural language processing research in recent years. In speech, a model pre-trained by self-supervi…
DUAL: Discrete Spoken Unit Adaptive Learning for Textless Spoken Question Answering
Guan-Ting Lin, Yung-Sung Chuang, Ho-Lam Chung +7
Spoken Question Answering (SQA) is to find the answer from a spoken document given a question, which is crucial for personal assistants when replying to the queries from the users.…
textless-lib: a Library for Textless Spoken Language Processing
Eugene Kharitonov, Jade Copet, Kushal Lakhotia +8
Textless spoken language processing research aims to extend the applicability of standard NLP toolset onto spoken language and languages with few or no textual resources. In this p…
Object Detection in Aerial Images: What Improves the Accuracy?
Hashmat Shadab Malik, Ikboljon Sobirov, Abdelrahman Mohamed
Object detection is a challenging and popular computer vision problem. The problem is even more challenging in aerial images due to significant variation in scale and viewpoint in…
Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction
Bowen Shi, Wei-Ning Hsu, Kushal Lakhotia +1
Video recordings of speech contain correlated audio and visual information, providing a strong signal for speech representation learning from the speaker's lip movements and the pr…
Robust Self-Supervised Audio-Visual Speech Recognition
Bowen Shi, Wei-Ning Hsu, Abdelrahman Mohamed
Audio-based automatic speech recognition (ASR) degrades significantly in noisy environments and is particularly vulnerable to interfering speech, as the model cannot determine whic…
Scaling ASR Improves Zero and Few Shot Learning
Alex Xiao, Weiyi Zheng, Gil Keren +6
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 s…
Textless Speech Emotion Conversion using Discrete and Decomposed Representations
Felix Kreuk, Adam Polyak, Jade Copet +7
Speech emotion conversion is the task of modifying the perceived emotion of a speech utterance while preserving the lexical content and speaker identity. In this study, we cast the…
Text-Free Prosody-Aware Generative Spoken Language Modeling
Eugene Kharitonov, Ann Lee, Adam Polyak +8
Speech pre-training has primarily demonstrated efficacy on classification tasks, while its capability of generating novel speech, similar to how GPT-2 can generate coherent paragra…
SUPERB: Speech processing Universal PERformance Benchmark
Shu-wen Yang, Po-Han Chi, Yung-Sung Chuang +17
Self-supervised learning (SSL) has proven vital for advancing research in natural language processing (NLP) and computer vision (CV). The paradigm pretrains a shared model on large…
Speech Resynthesis from Discrete Disentangled Self-Supervised Representations
Adam Polyak, Yossi Adi, Jade Copet +5
We propose using self-supervised discrete representations for the task of speech resynthesis. To generate disentangled representation, we separately extract low-bitrate representat…
Contrastive Semi-supervised Learning for ASR
Alex Xiao, Christian Fuegen, Abdelrahman Mohamed
Pseudo-labeling is the most adopted method for pre-training automatic speech recognition (ASR) models. However, its performance suffers from the supervised teacher model's degradin…
The Obata first eigenvalue theorems on a seven dimensional quaternionic contact manifold
Abdelrahman Mohamed, Dimiter Vassilev
We show that a compact quaternionic contact manifold of dimension seven that satisfies a Lichnerowicz-type lower Ricci-type bound and has the -function of any eigenfunction of t…
Unsupervised Cross-lingual Representation Learning for Speech Recognition
Alexis Conneau, Alexei Baevski, Ronan Collobert +2
This paper presents XLSR which learns cross-lingual speech representations by pretraining a single model from the raw waveform of speech in multiple languages. We build on wav2vec…