Speech Accent Classification
نویسنده
چکیده
English is one of the most prevalent languages in the world, and is the one most commonly used for communication between native speakers of different languages. As such, people from different regions around the world exhibit unique accents when speaking English. Classifying these accents can provide information about a speaker’s nationality and heritage to speech recognition systems, which are becoming increasingly common in day-to-day life. The data gleaned from a speaker’s accent can help speech recognition systems identify topics more relevant to the user, for the purposes of search results or advertisements.
منابع مشابه
FOREIGN ACCENT CLASSIFICATION USING SOURCE GENERATOR BASED PROSODIC FEATURES - Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Speaker accent is an important issue in the formulation of robust speaker independent recognition systems. Knowledge gained from a reliable accent classification approach could improve overall recognition performance. In this paper, a new algorithm is proposed for foreign accent classification of American English. A series of experimental studies are considered which focus on establishing how s...
متن کاملBeating Henry Higgins at His Own Game: A Markovian Approach to Dialectology
1. Introduction The performance of speech recognition algorithms degrades considerably due to speaker variability. Aside from gender, the largest cause for speaker variability is accent. If the accent of a speaker can be determined automatically, then accent-specific speech recognition models can be used, thereby increasing speech recognition accuracy. In this study, the problem of accent class...
متن کاملThe Effect of Listener Accent Background on Accent Perception and Comprehension
Variability of speaker accent is a challenge for effective human communication as well as speech technology including automatic speech recognition and accent identification. The motivation of this study is to contribute to a deeper understanding of accent variation across speakers from a cognitive perspective. The goal is to provide perceptual assessment of accent variation in native and Englis...
متن کاملA comparison of two unsupervised approaches to accent identification
The ability to automatically identify a speaker’s accent would be very useful for a speech recognition system as it would enable the system to use both a pronunciation dictionary and speech models specific to the accent, techniques which have been shown to improve accuracy. Here, we describe some experiments in unsupervised accent classification. Two techniques have been investigated to classif...
متن کاملPerception of Nonnative Accent: A Cross-Sectional Perspective Pilot Survey
Accent bias is a consequence of ethnocentrism. No studies have examined accent bias across educational levels in the U.S., much less across students and professionals in speech language pathology (SLP), a field that requires multicultural sensitivity training. This study examines nonnative accent perception among three groups—high schoolers, SLP students, and SLP professionals. One-hundred-and-...
متن کاملAssessing the efficacy of benchmarks for automatic speech accent recognition
Speech accents can possess valuable information about the speaker that can be used in intelligent multimedia-based human-computer interfaces. The performance of algorithms for automatic classification of accents is often evaluated using audio datasets that include recording samples of different people, representing different accents. Here we describe a method that can detect bias in accent data...
متن کامل