Implementation of realtime STRAIGHT speech manipulation system: Report on its first implementation

By Hideki Banno, Hiroaki Hata, Masanori Morise, Toru Takahashi, Toshio Irino, Hideki Kawahara. 2007

53 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Signal Processing

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. Hung-yi Lee
2. Andy T. Liu
3. Po-Chun Hsu
4. Zhiyong Wu
5. Chunxiao Xing
6. Yishuang Ning
7. Sheng He
8. Liang-Jie Zhang

In Signal Processing

1. Hung-yi Lee
2. Andy T. Liu
3. Po-Chun Hsu
4. Zhiyong Wu
5. Chunxiao Xing
6. Yishuang Ning
7. Sheng He
8. Chunhui Wang

Citations in the corpus

• A Review of Deep Learning Based Speech Synthesis (2019, methodology): “To improve the quality of the synthesized speech, STRAIGHT [34,35] is proposed and used in various studies, making it easy to manipulate speech.”
• Towards Robust Neural Vocoding for Speech Generation: A Survey (2019, background): “Traditionally, waveform can be vocoded from these acoustic or linguistic features using heuristic methods [9] or handcrafted vocoders [10, 11, 12].”
• Error Evaluation of an F0-Adaptive Spectral Envelope Estimator in Robustness against the Additive Noise and F0 Error (2015, background): “Several algorithms for high-quality speech synthesis and voice conversion have been proposed [4]–[8], and these algorithms would be effective for implementing real-time voice conversion systems [9], [10].”