Speech & Audio
Audio source separation, recognition, and understanding.
Our current research focuses on application of machine learning to estimation and inference problems in speech and audio processing. Topics include end-to-end speech recognition and enhancement, acoustic modeling and analysis, statistical dialog systems, as well as natural language understanding and adaptive multimodal interfaces.
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Researchers
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Awards
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AWARD Jonathan Le Roux elevated to IEEE Fellow Date: January 1, 2024
Awarded to: Jonathan Le Roux
MERL Contact: Jonathan Le Roux
Research Areas: Artificial Intelligence, Machine Learning, Speech & AudioBrief- MERL Distinguished Scientist and Speech & Audio Senior Team Leader Jonathan Le Roux has been elevated to IEEE Fellow, effective January 2024, "for contributions to multi-source speech and audio processing."
Mitsubishi Electric celebrated Dr. Le Roux's elevation and that of another researcher from the company, Dr. Shumpei Kameyama, with a worldwide news release on February 15.
Dr. Jonathan Le Roux has made fundamental contributions to the field of multi-speaker speech processing, especially to the areas of speech separation and multi-speaker end-to-end automatic speech recognition (ASR). His contributions constituted a major advance in realizing a practically usable solution to the cocktail party problem, enabling machines to replicate humans’ ability to concentrate on a specific sound source, such as a certain speaker within a complex acoustic scene—a long-standing challenge in the speech signal processing community. Additionally, he has made key contributions to the measures used for training and evaluating audio source separation methods, developing several new objective functions to improve the training of deep neural networks for speech enhancement, and analyzing the impact of metrics used to evaluate the signal reconstruction quality. Dr. Le Roux’s technical contributions have been crucial in promoting the widespread adoption of multi-speaker separation and end-to-end ASR technologies across various applications, including smart speakers, teleconferencing systems, hearables, and mobile devices.
IEEE Fellow is the highest grade of membership of the IEEE. It honors members with an outstanding record of technical achievements, contributing importantly to the advancement or application of engineering, science and technology, and bringing significant value to society. Each year, following a rigorous evaluation procedure, the IEEE Fellow Committee recommends a select group of recipients for elevation to IEEE Fellow. Less than 0.1% of voting members are selected annually for this member grade elevation.
- MERL Distinguished Scientist and Speech & Audio Senior Team Leader Jonathan Le Roux has been elevated to IEEE Fellow, effective January 2024, "for contributions to multi-source speech and audio processing."
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AWARD MERL team wins the Audio-Visual Speech Enhancement (AVSE) 2023 Challenge Date: December 16, 2023
Awarded to: Zexu Pan, Gordon Wichern, Yoshiki Masuyama, Francois Germain, Sameer Khurana, Chiori Hori, and Jonathan Le Roux
MERL Contacts: François Germain; Chiori Hori; Sameer Khurana; Jonathan Le Roux; Zexu Pan; Gordon Wichern
Research Areas: Artificial Intelligence, Machine Learning, Speech & AudioBrief- MERL's Speech & Audio team ranked 1st out of 12 teams in the 2nd COG-MHEAR Audio-Visual Speech Enhancement Challenge (AVSE). The team was led by Zexu Pan, and also included Gordon Wichern, Yoshiki Masuyama, Francois Germain, Sameer Khurana, Chiori Hori, and Jonathan Le Roux.
The AVSE challenge aims to design better speech enhancement systems by harnessing the visual aspects of speech (such as lip movements and gestures) in a manner similar to the brain’s multi-modal integration strategies. MERL’s system was a scenario-aware audio-visual TF-GridNet, that incorporates the face recording of a target speaker as a conditioning factor and also recognizes whether the predominant interference signal is speech or background noise. In addition to outperforming all competing systems in terms of objective metrics by a wide margin, in a listening test, MERL’s model achieved the best overall word intelligibility score of 84.54%, compared to 57.56% for the baseline and 80.41% for the next best team. The Fisher’s least significant difference (LSD) was 2.14%, indicating that our model offered statistically significant speech intelligibility improvements compared to all other systems.
- MERL's Speech & Audio team ranked 1st out of 12 teams in the 2nd COG-MHEAR Audio-Visual Speech Enhancement Challenge (AVSE). The team was led by Zexu Pan, and also included Gordon Wichern, Yoshiki Masuyama, Francois Germain, Sameer Khurana, Chiori Hori, and Jonathan Le Roux.
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AWARD MERL Intern and Researchers Win ICASSP 2023 Best Student Paper Award Date: June 9, 2023
Awarded to: Darius Petermann, Gordon Wichern, Aswin Subramanian, Jonathan Le Roux
MERL Contacts: Jonathan Le Roux; Gordon Wichern
Research Areas: Artificial Intelligence, Machine Learning, Speech & AudioBrief- Former MERL intern Darius Petermann (Ph.D. Candidate at Indiana University) has received a Best Student Paper Award at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023) for the paper "Hyperbolic Audio Source Separation", co-authored with MERL researchers Gordon Wichern and Jonathan Le Roux, and former MERL researcher Aswin Subramanian. The paper presents work performed during Darius's internship at MERL in the summer 2022. The paper introduces a framework for audio source separation using embeddings on a hyperbolic manifold that compactly represent the hierarchical relationship between sound sources and time-frequency features. Additionally, the code associated with the paper is publicly available at https://github.com/merlresearch/hyper-unmix.
ICASSP is the flagship conference of the IEEE Signal Processing Society (SPS). ICASSP 2023 was held in the Greek island of Rhodes from June 04 to June 10, 2023, and it was the largest ICASSP in history, with more than 4000 participants, over 6128 submitted papers and 2709 accepted papers. Darius’s paper was first recognized as one of the Top 3% of all papers accepted at the conference, before receiving one of only 5 Best Student Paper Awards during the closing ceremony.
- Former MERL intern Darius Petermann (Ph.D. Candidate at Indiana University) has received a Best Student Paper Award at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023) for the paper "Hyperbolic Audio Source Separation", co-authored with MERL researchers Gordon Wichern and Jonathan Le Roux, and former MERL researcher Aswin Subramanian. The paper presents work performed during Darius's internship at MERL in the summer 2022. The paper introduces a framework for audio source separation using embeddings on a hyperbolic manifold that compactly represent the hierarchical relationship between sound sources and time-frequency features. Additionally, the code associated with the paper is publicly available at https://github.com/merlresearch/hyper-unmix.
See All Awards for Speech & Audio -
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News & Events
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TALK [MERL Seminar Series 2024] Greta Tuckute presents talk titled Computational models of human auditory and language processing Date & Time: Wednesday, January 31, 2024; 12:00 PM
Speaker: Greta Tuckute, MIT
MERL Host: Sameer Khurana
Research Areas: Artificial Intelligence, Machine Learning, Speech & AudioAbstract- Advances in machine learning have led to powerful models for audio and language, proficient in tasks like speech recognition and fluent language generation. Beyond their immense utility in engineering applications, these models offer valuable tools for cognitive science and neuroscience. In this talk, I will demonstrate how these artificial neural network models can be used to understand how the human brain processes language. The first part of the talk will cover how audio neural networks serve as computational accounts for brain activity in the auditory cortex. The second part will focus on the use of large language models, such as those in the GPT family, to non-invasively control brain activity in the human language system.
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NEWS MERL co-organizes the 2023 Sound Demixing (SDX2023) Challenge and Workshop Date: January 23, 2023 - November 4, 2023
Where: International Symposium of Music Information Retrieval (ISMR)
MERL Contacts: Jonathan Le Roux; Gordon Wichern
Research Areas: Artificial Intelligence, Machine Learning, Speech & AudioBrief- MERL Speech & Audio team members Gordon Wichern and Jonathan Le Roux co-organized the 2023 Sound Demixing Challenge along with researchers from Sony, Moises AI, Audioshake, and Meta.
The SDX2023 Challenge was hosted on the AI Crowd platform and had a prize pool of $42,000 distributed to the winning teams across two tracks: Music Demixing and Cinematic Sound Demixing. A unique aspect of this challenge was the ability to test the audio source separation models developed by challenge participants on non-public songs from Sony Music Entertainment Japan for the music demixing track, and movie soundtracks from Sony Pictures for the cinematic sound demixing track. The challenge ran from January 23rd to May 1st, 2023, and had 884 participants distributed across 68 teams submitting 2828 source separation models. The winners will be announced at the SDX2023 Workshop, which will take place as a satellite event at the International Symposium of Music Information Retrieval (ISMR) in Milan, Italy on November 4, 2023.
MERL’s contribution to SDX2023 focused mainly on the cinematic demixing track. In addition to sponsoring the prizes awarded to the winning teams for that track, the baseline system and initial training data were MERL’s Cocktail Fork separation model and Divide and Remaster dataset, respectively. MERL researchers also contributed to a Town Hall kicking off the challenge, co-authored a scientific paper describing the challenge outcomes, and co-organized the SDX2023 Workshop.
- MERL Speech & Audio team members Gordon Wichern and Jonathan Le Roux co-organized the 2023 Sound Demixing Challenge along with researchers from Sony, Moises AI, Audioshake, and Meta.
See All News & Events for Speech & Audio -
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Research Highlights
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Recent Publications
- "SPECDIFF-GAN: A SPECTRALLY-SHAPED NOISE DIFFUSION GAN FOR SPEECH AND MUSIC SYNTHESIS", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), March 2024.BibTeX TR2024-013 PDF
- @inproceedings{Baoueb2024mar,
- author = {Baoueb, Teysir and Liu, Haocheng and Fontaine, Mathieu and Le Roux, Jonathan and Richard, Gaël},
- title = {SPECDIFF-GAN: A SPECTRALLY-SHAPED NOISE DIFFUSION GAN FOR SPEECH AND MUSIC SYNTHESIS},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2024,
- month = mar,
- url = {https://www.merl.com/publications/TR2024-013}
- }
, - "Wi-Fi based Indoor Monitoring Enhanced by Multimodal Fusion", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), March 2024.BibTeX TR2024-012 PDF
- @inproceedings{Hori2024mar,
- author = {Hori, Chiori and Wang, Pu and Rahman, Mahbub and Vaca-Rubio, Cristian and Khurana, Sameer and Cherian, Anoop and Le Roux, Jonathan},
- title = {Wi-Fi based Indoor Monitoring Enhanced by Multimodal Fusion},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2024,
- month = mar,
- url = {https://www.merl.com/publications/TR2024-012}
- }
, - "GLA-GRAD: A GRIFFIN-LIM EXTENDED WAVEFORM GENERATION DIFFUSION MODEL", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), March 2024.BibTeX TR2024-014 PDF
- @inproceedings{Liu2024mar,
- author = {Liu, Haocheng and Baoueb, Teysir and Fontaine, Mathieu and Le Roux, Jonathan and Richard, Gaël},
- title = {GLA-GRAD: A GRIFFIN-LIM EXTENDED WAVEFORM GENERATION DIFFUSION MODEL},
- booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
- year = 2024,
- month = mar,
- url = {https://www.merl.com/publications/TR2024-014}
- }
, - "TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings", IEEE/ACM Transactions on Audio, Speech, and Language Processing, DOI: 10.1109/TASLP.2024.3350887, Vol. 32, pp. 1185-1197, February 2024.BibTeX TR2024-006 PDF
- @article{Boeddeker2024feb,
- author = {Boeddeker, Christoph and Subramanian, Aswin Shanmugam and Wichern, Gordon and Haeb-Umbach, Reinhold and Le Roux, Jonathan},
- title = {TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings},
- journal = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},
- year = 2024,
- volume = 32,
- pages = {1185--1197},
- month = feb,
- doi = {10.1109/TASLP.2024.3350887},
- issn = {2329-9304},
- url = {https://www.merl.com/publications/TR2024-006}
- }
, - "CAVEN: An Embodied Conversational Agent for Efficient Audio-Visual Navigation in Noisy Environments", AAAI Conference on Artificial Intelligence, December 2023.BibTeX TR2023-154 PDF
- @inproceedings{Liu2023dec2,
- author = {Liu, Xiulong and Paul, Sudipta and Chatterjee, Moitreya and Cherian, Anoop},
- title = {CAVEN: An Embodied Conversational Agent for Efficient Audio-Visual Navigation in Noisy Environments},
- booktitle = {AAAI Conference on Artificial Intelligence},
- year = 2023,
- month = dec,
- url = {https://www.merl.com/publications/TR2023-154}
- }
, - "Scenario-Aware Audio-Visual TF-GridNet for Target Speech Extraction", IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), DOI: 10.1109/ASRU57964.2023.10389618, December 2023.BibTeX TR2023-152 PDF
- @inproceedings{Pan2023dec2,
- author = {Pan, Zexu and Wichern, Gordon and Masuyama, Yoshiki and Germain, François G and Khurana, Sameer and Hori, Chiori and Le Roux, Jonathan},
- title = {Scenario-Aware Audio-Visual TF-GridNet for Target Speech Extraction},
- booktitle = {IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)},
- year = 2023,
- month = dec,
- doi = {10.1109/ASRU57964.2023.10389618},
- isbn = {979-8-3503-0689-7},
- url = {https://www.merl.com/publications/TR2023-152}
- }
, - "Sound3DVDet: 3D Sound Source Detection using Multiview Microphone Array and RGB Images", IEEE Winter Conference on Applications of Computer Vision (WACV), December 2023.BibTeX TR2023-144 PDF
- @inproceedings{He2023dec,
- author = {He, Yuhang and Shin, Sangyun and Cherian, Anoop and Markham, Andrew and Trigon, Niki},
- title = {Sound3DVDet: 3D Sound Source Detection using Multiview Microphone Array and RGB Images},
- booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},
- year = 2023,
- month = dec,
- url = {https://www.merl.com/publications/TR2023-144}
- }
, - "On the Use of Pretrained Deep Audio Encoders for Automated Audio Captioning Tasks", International Symposium on Future Active Safety Technology toward zero traffic accidents (FAST-zero), November 2023.BibTeX TR2023-141 PDF
- @inproceedings{Wu2023nov,
- author = {Wu, Shih-Lun and Chang, Xuankai and Wichern, Gordon and Jung, Jee-weon and Germain, François G and Le Roux, Jonathan and Watanabe, Shinji},
- title = {On the Use of Pretrained Deep Audio Encoders for Automated Audio Captioning Tasks},
- booktitle = {International Symposium on Future Active Safety Technology toward zero traffic accidents (FAST-zero)},
- year = 2023,
- month = nov,
- url = {https://www.merl.com/publications/TR2023-141}
- }
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- "SPECDIFF-GAN: A SPECTRALLY-SHAPED NOISE DIFFUSION GAN FOR SPEECH AND MUSIC SYNTHESIS", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), March 2024.
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