P.563—The ITU-T Standard for Single-Ended Speech Quality Assessment

By L. Malfait, J. Berger, M. Kastner. 2006

228 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Mechanics, 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. Xu Tan
2. Tao Qin
3. Sheng Zhao
4. Tie-Yan Liu
5. Frank K. Soong
6. Yichong Leng
7. Xavier Serra
8. Eduardo Fonseca

In Computational Mechanics

1. Jordi Pons
2. Tao Qin
3. Xavier Serra
4. Björn Schuller

In Signal Processing

1. Eduardo Fonseca
2. Xavier Serra
3. Xu Tan
4. Tao Qin
5. Frederic Font
6. Xavier Favory
7. Jordi Pons
8. Sheng Zhao

Citations in the corpus

• FSD50K: An Open Dataset of Human-Labeled Sound Events (2020, methodology): “We extracted the global SNR for FSD50K and AudioSet (its eval set and balanced train set) using the ITU-T P.563 [82].”
• An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era (2022, background): “P.563 [174] is often used to evaluate the quality of generated signals.”
• MBNET: MOS Prediction for Synthesized Speech with Mean-Bias Network (2021, background): “Existing objective metrics [7, 8, 9, 10] can only reflect speech quality from some certain aspects.”