The variety of accents has posed a big challenge to speech recognition. The Accented
English Speech Recognition Challenge (AESRC2020) is designed for providing a common …

In this paper, we propose a single multi-task learning framework to perform End-to-End
(E2E) speech recognition (ASR) and accent recognition (AR) simultaneously. The proposed …

Automatic accent classification is an active research field concerning speech processing. It
can be useful to identify a speaker's region of origin, which can be applied in police …

This paper describes the AISpeech-SJTU system for the accent identification track of the
Interspeech-2020 Accented English Speech Recognition Challenge. In this challenge track …

In this paper, we propose an end-to-end (E2E) dialect identification system trained using
transfer learning from a multilingual automatic speech recognition (ASR) model. This is also …

Automatic pronunciation error detection (APED) plays an important role in the domain of
language learning. As for the previous ASR-based APED methods, the decoded results …

Social background profiling of speakers is heavily used in areas, such as, speech forensics,
and tuning speech recognition for accuracy improvement. This article provides a survey of …

Accent or dialect is one of the hot topics of emerging technology in speech processing. In an
audio recording, extracting accent clues from a speech signal can help investigators to have …

Understanding accent is an issue which can derail any human-machine interaction. Accent
classification makes this task easier by identifying the accent being spoken by a person so …

Automatic pronunciation evaluation plays an important role in pronunciation training and
second language education. This field draws heavily on concepts from automatic speech …