A review of deep learning techniques for speech processing
The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …
learning. The use of multiple processing layers has enabled the creation of models capable …
A survey on neural speech synthesis
Text to speech (TTS), or speech synthesis, which aims to synthesize intelligible and natural
speech given text, is a hot research topic in speech, language, and machine learning …
speech given text, is a hot research topic in speech, language, and machine learning …
Generative pre-training for speech with autoregressive predictive coding
Learning meaningful and general representations from unannotated speech that are
applicable to a wide range of tasks remains challenging. In this paper we propose to use …
applicable to a wide range of tasks remains challenging. In this paper we propose to use …
Lrspeech: Extremely low-resource speech synthesis and recognition
Speech synthesis (text to speech, TTS) and recognition (automatic speech recognition, ASR)
are important speech tasks, and require a large amount of text and speech pairs for model …
are important speech tasks, and require a large amount of text and speech pairs for model …
Low-resource expressive text-to-speech using data augmentation
While recent neural text-to-speech (TTS) systems perform remarkably well, they typically
require a substantial amount of recordings from the target speaker reading in the desired …
require a substantial amount of recordings from the target speaker reading in the desired …
One model, many languages: Meta-learning for multilingual text-to-speech
T Nekvinda, O Dušek - arXiv preprint arXiv:2008.00768, 2020 - arxiv.org
We introduce an approach to multilingual speech synthesis which uses the meta-learning
concept of contextual parameter generation and produces natural-sounding multilingual …
concept of contextual parameter generation and produces natural-sounding multilingual …
A systematic review and analysis of multilingual data strategies in text-to-speech for low-resource languages
We provide a systematic review of past studies that use multilingual data for text-to-speech
(TTS) of low-resource languages (LRLs). We focus on the strategies used by these studies …
(TTS) of low-resource languages (LRLs). We focus on the strategies used by these studies …
Open-source multi-speaker speech corpora for building Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu speech synthesis systems
F He, SHC Chu, O Kjartansson, C Rivera… - Proceedings of the …, 2020 - aclanthology.org
We present free high quality multi-speaker speech corpora for Gujarati, Kannada,
Malayalam, Marathi, Tamil and Telugu, which are six of the twenty two official languages of …
Malayalam, Marathi, Tamil and Telugu, which are six of the twenty two official languages of …
Requirements and motivations of low-resource speech synthesis for language revitalization
This paper describes the motivation and development of speech synthesis systems for the
purposes of language revitalization. By building speech synthesis systems for three …
purposes of language revitalization. By building speech synthesis systems for three …
Language-agnostic meta-learning for low-resource text-to-speech with articulatory features
While neural text-to-speech systems perform remarkably well in high-resource scenarios,
they cannot be applied to the majority of the over 6,000 spoken languages in the world due …
they cannot be applied to the majority of the over 6,000 spoken languages in the world due …