Speaking Speed Control of End-to-End Speech Synthesis using Sentence-Level Conditioning

By Jaesung Bae, Hanbin Bae, Young-Sun Joo, Gyeong-Hoon Lee, Hoon-Young Cho. 2020

19 citations recorded by the source corpus.

This paper proposes a controllable end-to-end text-to-speech (TTS) system to control the speaking speed (speed-controllable TTS; SCTTS) of synthesized speech with sentence-level speaking-rate value as an additional input. The speaking-rate value, the ratio of the number of input phonemes to the length of input speech, is adopted in the proposed system to control the speaking speed. Furthermore, the proposed SCTTS system can control the speaking speed while retaining other speech attributes, such as the pitch, by adopting the global style token-based style encoder. The proposed SCTTS does not require any additional well-trained model or an external speech database to extract phoneme-level duration information and can be trained in an end-to-end manner. In addition, our listening tests on fast-, normal-, and slow-speed speech showed that the SCTTS can generate more natural speech than other phoneme duration control approaches which increase or decrease duration at the same rate for the entire sentence, especially in the case of slow-speed speech.

Subfields: Artificial Intelligence, Experimental and Cognitive Psychology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Xu Tan
2. Tao Qin
3. Tie-Yan Liu
4. Sheng Zhao
5. Frank K. Soong
6. Yichong Leng
7. Xuejiao Tan
8. Yi Ren

In Experimental and Cognitive Psychology

1. Tao Qin
2. Yichong Leng
3. Frank K. Soong
4. Tie-Yan Liu
5. Sheng Zhao
6. Xu Tan

Citations in the corpus

• A Survey on Neural Speech Synthesis (2021, methodology): “In this subsection, we review techniques on disentangling [218, 117, 275], controlling [353, 180, 240, 13, 267, 343, 192], and transferring [150, 131, 393, 6] variation information, as shown in Table 15.”
• Prompttts: Controllable Text-To-Speech With Text Descriptions (2022, background): “Previous works on controllable TTS focus on controlling specific style factors: prosody control with word-level prosody tags [9], speaking speed control with sentence-level speaking-rate [10], and”