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Found 9 papers, 1 papers with code
Stutter-TTS: Controlled Synthesis and Improved Recognition of Stuttered Speech
By fine-tuning an ASR model on synthetic stuttered speech we are able to reduce word error by 5. 7% relative on stuttered utterances, with only minor (<0. 2% relative) degradation for fluent utterances.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Peking Opera Synthesis via Duration Informed Attention Network
In this work, we propose to deal with this issue and synthesize expressive Peking Opera singing from the music score based on the Duration Informed Attention Network (DurIAN) framework.
Synthesising Expressiveness in Peking Opera via Duration Informed Attention Network
This paper presents a method that generates expressive singing voice of Peking opera.
Learning Singing From Speech
The proposed algorithm first integrate speech and singing synthesis into a unified framework, and learns universal speaker embeddings that are shareable between speech and singing synthesis tasks.
PitchNet: Unsupervised Singing Voice Conversion with Pitch Adversarial Network
However, the converted singing voice can be easily out of key, showing that the existing approach cannot model the pitch information precisely.
Minimum Bayes Risk Training of RNN-Transducer for End-to-End Speech Recognition
In this work, we propose minimum Bayes risk (MBR) training of RNN-Transducer (RNN-T) for end-to-end speech recognition.
DurIAN: Duration Informed Attention Network For Multimodal Synthesis
In this paper, we present a generic and robust multimodal synthesis system that produces highly natural speech and facial expression simultaneously.
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
We consider the problem of training speech recognition systems without using any labeled data, under the assumption that the learner can only access to the input utterances and a phoneme language model estimated from a non-overlapping corpus.
UTD-CRSS Systems for 2016 NIST Speaker Recognition Evaluation
This document briefly describes the systems submitted by the Center for Robust Speech Systems (CRSS) from The University of Texas at Dallas (UTD) to the 2016 National Institute of Standards and Technology (NIST) Speaker Recognition Evaluation (SRE).
