Audio and acoustics

Project

Text to Speech

We are working on neural network based text to speech (TTS). including acoustic model, vocoder, frontend, and end-to-end text-to-wave model. Our research works have been transferred in Microsoft Azure TTS service to improve the product…

Group

LEAP – Language, Learning, Audio, Privacy

Scientists and engineers in the LEAP (Language, Learning, Audio, Privacy) research area make and harness advances in machine learning, natural language processing, and signal processing to: We advance the state-of-the-art in AI while providing practical…

Publication

DNSMOS: A Non-Intrusive Perceptual Objective Speech Quality metric to evaluate Noise Suppressors

Chandan K. A. Reddy, Vishak Gopal, Ross Cutler

2020 International Conference on Acoustics, Speech, and Signal Processing | October 2020

Publication

Joint Speaker Counting, Speech Recognition, and Speaker Identification for Overlapped Speech of Any Number of Speakers

Naoyuki Kanda, Yashesh Gaur, Xiaofei Wang, Zhong Meng, Zhuo Chen, Tianyan Zhou, Takuya Yoshioka

Interspeech 2020 | October 2020

Project Project

Publication

Discriminative Transfer Learning for Optimizing ASR and Semantic Labeling in Task-oriented Spoken Dialog

Yao Qian, Yu Shi, Michael Zeng

InterSpeech2020 | October 2020

Publication

Serialized Output Training for End-to-End Overlapped Speech Recognition

Naoyuki Kanda, Yashesh Gaur, Xiaofei Wang, Zhong Meng, Takuya Yoshioka

Interspeech 2020 | October 2020

Project Project

Publication

An Open Source Implementation of ITU-T Recommendation P.808 with Validation

Babak Naderi, Ross Cutler

2020 Conference of the International Speech Communication Association | October 2020

Publication

DNN No-Reference PSTN Speech Quality Prediction

Gabriel Mittag, Ross Cutler, Yasaman Hosseinkashi, Michael Revow, Sriram Srinivasan, Naglakshmi Chande, Robert Aichner

2020 Conference of the International Speech Communication Association | October 2020

Publication

The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results

Chandan K. A. Reddy, Vishak Gopal, Ross Cutler, Ebrahim Beyrami, Roger Cheng, Harishchandra Dubey, Sergiy Matusevych, Robert Aichner, Ashkan Aazami, Sebastian Braun, Puneet Rana, Sriram Srinivasan, Johannes Gehrke

Interspeech | October 2020

Project

Group

AI For Good Lab

The Microsoft AI For Good team helps researchers and organizations reach solutions on some of the world’s biggest problems. Providing technology, resources, and expertise to empower those working to solve humanitarian issues to create a…