216 citations · 556 across the 81 of their papers we have counts for
12 papers · 1 filter
Fine-grained activity recognition for assembly videos
Jonathan D. Jones, Cathryn Cortesa, Amy Shelton +3
In this paper we address the task of recognizing assembly actions as a structure (e.g. a piece of furniture or a toy block tower) is built up from a set of primitive objects. Recog…
Multi-class Spectral Clustering with Overlaps for Speaker Diarization
Desh Raj, Zili Huang, Sanjeev Khudanpur
This paper describes a method for overlap-aware speaker diarization. Given an overlap detector and a speaker embedding extractor, our method performs spectral clustering of segment…
DOVER-Lap: A Method for Combining Overlap-aware Diarization Outputs
Desh Raj, Leibny Paola Garcia-Perera, Zili Huang +4
Several advances have been made recently towards handling overlapping speech for speaker diarization. Since speech and natural language tasks often benefit from ensemble techniques…
Frustratingly Easy Noise-aware Training of Acoustic Models
Desh Raj, Jesus Villalba, Daniel Povey +1
Environmental noises and reverberation have a detrimental effect on the performance of automatic speech recognition (ASR) systems. Multi-condition training of neural network-based…
Training Noisy Single-Channel Speech Separation With Noisy Oracle Sources: A Large Gap and A Small Step
Matthew Maciejewski, Jing Shi, Shinji Watanabe +1
As the performance of single-channel speech separation systems has improved, there has been a desire to move to more challenging conditions than the clean, near-field speech that i…
Neural Language Modeling With Implicit Cache Pointers
Ke Li, Daniel Povey, Sanjeev Khudanpur
A cache-inspired approach is proposed for neural language models (LMs) to improve long-range dependency and better predict rare words from long contexts. This approach is a simpler…
Mixture of Speaker-type PLDAs for Children's Speech Diarization
Jiamin Xie, Suzanna Sia, Paola Garcia +2
In diarization, the PLDA is typically used to model an inference structure which assumes the variation in speech segments be induced by various speakers. The speaker variation is t…
Efficient MDI Adaptation for n-gram Language Models
Ruizhe Huang, Ke Li, Ashish Arora +2
This paper presents an efficient algorithm for n-gram language model adaptation under the minimum discrimination information (MDI) principle, where an out-of-domain language model…
The JHU Multi-Microphone Multi-Speaker ASR System for the CHiME-6 Challenge
Ashish Arora, Desh Raj, Aswin Shanmugam Subramanian +7
This paper summarizes the JHU team's efforts in tracks 1 and 2 of the CHiME-6 challenge for distant multi-microphone conversational speech diarization and recognition in everyday h…
PyChain: A Fully Parallelized PyTorch Implementation of LF-MMI for End-to-End ASR
Yiwen Shao, Yiming Wang, Daniel Povey +1
We present PyChain, a fully parallelized PyTorch implementation of end-to-end lattice-free maximum mutual information (LF-MMI) training for the so-called \emph{chain models} in the…
Wake Word Detection with Alignment-Free Lattice-Free MMI
Yiming Wang, Hang Lv, Daniel Povey +2
Always-on spoken language interfaces, e.g. personal digital assistants, rely on a wake word to start processing spoken input. We present novel methods to train a hybrid DNN/HMM wak…
Speaker Diarization with Region Proposal Network
Zili Huang, Shinji Watanabe, Yusuke Fujita +4
Speaker diarization is an important pre-processing step for many speech applications, and it aims to solve the "who spoke when" problem. Although the standard diarization systems c…