788 citations · 2.9k across the 245 of their papers we have counts for
257 papers
Acoustic modeling for Overlapping Speech Recognition: JHU Chime-5 Challenge System
Vimal Manohar, Szu-Jui Chen, Zhiqi Wang +3
This paper summarizes our acoustic modeling efforts in the Johns Hopkins University speech recognition system for the CHiME-5 challenge to recognize highly-overlapped dinner party…
Reproducing Whisper-Style Training Using an Open-Source Toolkit and Publicly Available Data
Yifan Peng, Jinchuan Tian, Brian Yan +13
Pre-training speech models on large volumes of data has achieved remarkable success. OpenAI Whisper is a multilingual multitask model trained on 680k hours of supervised speech dat…
Segment-Level Vectorized Beam Search Based on Partially Autoregressive Inference
Masao Someki, Nicholas Eng, Yosuke Higuchi +1
Attention-based encoder-decoder models with autoregressive (AR) decoding have proven to be the dominant approach for automatic speech recognition (ASR) due to their superior accura…
Joint Prediction and Denoising for Large-scale Multilingual Self-supervised Learning
William Chen, Jiatong Shi, Brian Yan +6
Multilingual self-supervised learning (SSL) has often lagged behind state-of-the-art (SOTA) methods due to the expenses and complexity required to handle many languages. This furth…
Cross-Modal Multi-Tasking for Speech-to-Text Translation via Hard Parameter Sharing
Brian Yan, Xuankai Chang, Antonios Anastasopoulos +2
Recent works in end-to-end speech-to-text translation (ST) have proposed multi-tasking methods with soft parameter sharing which leverage machine translation (MT) data via secondar…
Exploring Speech Recognition, Translation, and Understanding with Discrete Speech Units: A Comparative Study
Xuankai Chang, Brian Yan, Kwanghee Choi +14
Speech signals, typically sampled at rates in the tens of thousands per second, contain redundancies, evoking inefficiencies in sequence modeling. High-dimensional speech features…
Enhancing End-to-End Conversational Speech Translation Through Target Language Context Utilization
Amir Hussein, Brian Yan, Antonios Anastasopoulos +2
Incorporating longer context has been shown to benefit machine translation, but the inclusion of context in end-to-end speech translation (E2E-ST) remains under-studied. To bridge…
Speech collage: code-switched audio generation by collaging monolingual corpora
Amir Hussein, Dorsa Zeinali, Ondřej Klejch +6
Designing effective automatic speech recognition (ASR) systems for Code-Switching (CS) often depends on the availability of the transcribed CS resources. To address data scarcity,…
Towards Practical and Efficient Image-to-Speech Captioning with Vision-Language Pre-training and Multi-modal Tokens
Minsu Kim, Jeongsoo Choi, Soumi Maiti +3
In this paper, we propose methods to build a powerful and efficient Image-to-Speech captioning (Im2Sp) model. To this end, we start with importing the rich knowledge related to ima…
The Multimodal Information Based Speech Processing (MISP) 2023 Challenge: Audio-Visual Target Speaker Extraction
Shilong Wu, Chenxi Wang, Hang Chen +13
Previous Multimodal Information based Speech Processing (MISP) challenges mainly focused on audio-visual speech recognition (AVSR) with commendable success. However, the most advan…
Toward Universal Speech Enhancement for Diverse Input Conditions
Wangyou Zhang, Kohei Saijo, Zhong-Qiu Wang +2
The past decade has witnessed substantial growth of data-driven speech enhancement (SE) techniques thanks to deep learning. While existing approaches have shown impressive performa…
Improving Audio Captioning Models with Fine-grained Audio Features, Text Embedding Supervision, and LLM Mix-up Augmentation
Shih-Lun Wu, Xuankai Chang, Gordon Wichern +4
Automated audio captioning (AAC) aims to generate informative descriptions for various sounds from nature and/or human activities. In recent years, AAC has quickly attracted resear…
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…
Dynamic-SUPERB: Towards A Dynamic, Collaborative, and Comprehensive Instruction-Tuning Benchmark for Speech
Chien-yu Huang, Ke-Han Lu, Shih-Heng Wang +12
Text language models have shown remarkable zero-shot capability in generalizing to unseen tasks when provided with well-formulated instructions. However, existing studies in speech…
Decoder-only Architecture for Speech Recognition with CTC Prompts and Text Data Augmentation
Emiru Tsunoo, Hayato Futami, Yosuke Kashiwagi +2
Collecting audio-text pairs is expensive; however, it is much easier to access text-only data. Unless using shallow fusion, end-to-end automatic speech recognition (ASR) models req…
Visual Speech Recognition for Languages with Limited Labeled Data using Automatic Labels from Whisper
Jeong Hun Yeo, Minsu Kim, Shinji Watanabe +1
This paper proposes a powerful Visual Speech Recognition (VSR) method for multiple languages, especially for low-resource languages that have a limited number of labeled data. Diff…
Voxtlm: unified decoder-only models for consolidating speech recognition/synthesis and speech/text continuation tasks
Soumi Maiti, Yifan Peng, Shukjae Choi +3
We propose a decoder-only language model, VoxtLM, that can perform four tasks: speech recognition, speech synthesis, text generation, and speech continuation. VoxtLM integrates tex…
Exploring the Integration of Speech Separation and Recognition with Self-Supervised Learning Representation
Yoshiki Masuyama, Xuankai Chang, Wangyou Zhang +5
Neural speech separation has made remarkable progress and its integration with automatic speech recognition (ASR) is an important direction towards realizing multi-speaker ASR. Thi…
BASS: Block-wise Adaptation for Speech Summarization
Roshan Sharma, Kenneth Zheng, Siddhant Arora +3
End-to-end speech summarization has been shown to improve performance over cascade baselines. However, such models are difficult to train on very large inputs (dozens of minutes or…
The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios
Samuele Cornell, Matthew Wiesner, Shinji Watanabe +8
The CHiME challenges have played a significant role in the development and evaluation of robust automatic speech recognition (ASR) systems. We introduce the CHiME-7 distant ASR (DA…
Deep Speech Synthesis from MRI-Based Articulatory Representations
Peter Wu, Tingle Li, Yijing Lu +6
In this paper, we study articulatory synthesis, a speech synthesis method using human vocal tract information that offers a way to develop efficient, generalizable and interpretabl…
Exploration on HuBERT with Multiple Resolutions
Jiatong Shi, Yun Tang, Hirofumi Inaguma +3
Hidden-unit BERT (HuBERT) is a widely-used self-supervised learning (SSL) model in speech processing. However, we argue that its fixed 20ms resolution for hidden representations wo…
Tensor decomposition for minimization of E2E SLU model toward on-device processing
Yosuke Kashiwagi, Siddhant Arora, Hayato Futami +6
Spoken Language Understanding (SLU) is a critical speech recognition application and is often deployed on edge devices. Consequently, on-device processing plays a significant role…
Efficient Sequence Transduction by Jointly Predicting Tokens and Durations
Hainan Xu, Fei Jia, Somshubra Majumdar +3
This paper introduces a novel Token-and-Duration Transducer (TDT) architecture for sequence-to-sequence tasks. TDT extends conventional RNN-Transducer architectures by jointly pred…