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20182021
most citedTraditional Machine Learning for Pitch Detection

32 citations · 35 across the 4 of their papers we have counts for

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Showing eess.ASShow all

5 papers · 1 filter

eess.AS2021

Enhancing audio quality for expressive Neural Text-to-Speech

Abdelhamid Ezzerg, Adam Gabrys, Bartosz Putrycz +7

Artificial speech synthesis has made a great leap in terms of naturalness as recent Text-to-Speech (TTS) systems are capable of producing speech with similar quality to human recor…

eess.AS20212 cited

Universal Neural Vocoding with Parallel WaveNet

Yunlong Jiao, Adam Gabrys, Georgi Tinchev +3

We present a universal neural vocoder based on Parallel WaveNet, with an additional conditioning network called Audio Encoder. Our universal vocoder offers real-time high-quality s…

eess.AS2020

CopyCat: Many-to-Many Fine-Grained Prosody Transfer for Neural Text-to-Speech

Sri Karlapati, Alexis Moinet, Arnaud Joly +3

Prosody Transfer (PT) is a technique that aims to use the prosody from a source audio as a reference while synthesising speech. Fine-grained PT aims at capturing prosodic aspects l…

eess.AS2019

Fine-grained robust prosody transfer for single-speaker neural text-to-speech

Viacheslav Klimkov, Srikanth Ronanki, Jonas Rohnke +1

We present a neural text-to-speech system for fine-grained prosody transfer from one speaker to another. Conventional approaches for end-to-end prosody transfer typically use eithe…

eess.AS2018

Comprehensive evaluation of statistical speech waveform synthesis

Thomas Merritt, Bartosz Putrycz, Adam Nadolski +10

Statistical TTS systems that directly predict the speech waveform have recently reported improvements in synthesis quality. This investigation evaluates Amazon's statistical speech…