title: ÐÐ²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ðµ Ð°ÐºÑÐµÐ½ÑÐ° Ð¿Ð¾ ÑÐµÑÐ¸ Ð½Ð° Ð¸Ð½Ð¾ÑÑÑÐ°Ð½Ð½Ð¾Ð¼ ÑÐ·ÑÐºÐµ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Automatic accent recognition in foreign language speech
Creators: name: ÐÐµÑÐ½Ð¸ÑÐ°Ñ, ÐÐ°ÑÐ¸Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2021
Subjects: Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¾Ðµ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ðµ ÑÐµÑÐ¸
Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¾Ð¿ÑÐµÐ´ÐµÐ»ÐµÐ½Ð¸Ðµ Ð°ÐºÑÐµÐ½ÑÐ°
ÑÐ²ÐµÑÑÐ¾ÑÐ½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð¸Ð·Ð²Ð»ÐµÑÐµÐ½Ð¸Ðµ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð²
automatic speech recognition
automatic accent recognition
convolutional neural networks
feature extraction

description: ÐÑÐ¾Ð±Ð»ÐµÐ¼Ð° ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð°ÐºÑÐµÐ½ÑÐ° Ð¿Ð¾Ð»ÑÑÐ¸Ð»Ð° Ð±Ð¾Ð»ÑÑÐ¾Ðµ Ð²Ð½Ð¸Ð¼Ð°Ð½Ð¸Ðµ Ñ ÑÐ°Ð·Ð²Ð¸ÑÐ¸ÐµÐ¼ ASR ÑÐ¸ÑÑÐµÐ¼, Ð¿Ð¾ÑÐºÐ¾Ð»ÑÐºÑ Ð¾Ð±ÑÑÐ½ÑÐµ Ð°ÐºÑÑÑÐ¸ÑÐµÑÐºÐ¸Ðµ ÑÐ·ÑÐºÐ¾Ð²ÑÐµ Ð¼Ð¾Ð´ÐµÐ»Ð¸, Ð°Ð´Ð°Ð¿ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐµ Ð´Ð»Ñ ÑÐ¾Ð¾ÑÐ²ÐµÑÑÑÐ²Ð¸Ñ ÑÑÐ°Ð½Ð´Ð°ÑÑÐ½Ð¾Ð¼Ñ ÑÐ·ÑÐºÐ¾Ð²Ð¾Ð¼Ñ ÐºÐ¾ÑÐ¿ÑÑÑ, Ð½Ðµ ÑÐ´Ð¾Ð²Ð»ÐµÑÐ²Ð¾ÑÑÑÑ ÑÑÐµÐ±Ð¾Ð²Ð°Ð½Ð¸ÑÐ¼ Ðº ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¿ÑÐ¸ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ð¸ Ðº Ð°ÐºÑÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸. ÐÐ¾ÑÐºÐ¾Ð»ÑÐºÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÑ CNN ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ñ Ð¿ÑÐ¸ ÑÐµÑÐµÐ½Ð¸Ð¸ Ð·Ð°Ð´Ð°Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð°ÐºÑÐµÐ½ÑÐ°, ÑÐ°ÐºÐ°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð° Ð² Ð´Ð°Ð½Ð½Ð¾Ð¹ Ð²ÑÐ¿ÑÑÐºÐ½Ð¾Ð¹ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ. ÐÐ¾Ð´ÐµÐ»Ñ Ð±ÑÐ»Ð° Ð¾Ð±ÑÑÐµÐ½Ð° Ð½Ð° ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ°Ñ Ð°ÑÐ´Ð¸Ð¾ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð², Ð¸Ð·Ð²Ð»ÐµÑÐµÐ½Ð½ÑÑ Ð¸Ð· Ð·Ð°Ð¿Ð¸ÑÐµÐ¹ Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ Speech Accent Archive. Ð­ÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ°Ð»ÑÐ½Ð¾ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð½Ð¾, ÑÑÐ¾ Ð´Ð¾Ð±Ð°Ð²Ð»ÐµÐ½Ð¸Ðµ Ðº MFCC Ð´Ð¾Ð¿Ð¾Ð»Ð½Ð¸ÑÐµÐ»ÑÐ½Ð¾Ð¹ Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¸ Ð¾Ð± Ð°ÑÐ´Ð¸Ð¾ÑÐ¸Ð³Ð½Ð°Ð»Ð°Ñ Ð² Ð½ÐµÐºÐ¾ÑÐ¾ÑÑÑ ÑÐ»ÑÑÐ°ÑÑ Ð¿ÑÐ¸Ð²Ð¾Ð´Ð¸Ñ Ðº Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ ÑÐ¾ÑÐ½Ð¾ÑÑÐ¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð°ÐºÑÐµÐ½ÑÐ°. ÐÐ¾Ð»ÑÑÐµÐ½Ð¾, ÑÑÐ¾ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¼ÐµÐ»-ÑÐ¿ÐµÐºÑÑÐ¾Ð³ÑÐ°Ð¼Ð¼ Ñ Ð»Ð¸Ð½ÐµÐ¹Ð½ÑÐ¼ Ð¼Ð°ÑÑÑÐ°Ð±Ð¾Ð¼ Ð°Ð¼Ð¿Ð»Ð¸ÑÑÐ´Ñ Ð´Ð»Ñ ÑÐ°ÑÑÐ¼Ð°ÑÑÐ¸Ð²Ð°ÐµÐ¼Ð¾Ð³Ð¾ Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ ÑÐ²Ð»ÑÐµÑÑÑ Ð±Ð¾Ð»ÐµÐµ ÑÑÑÐµÐºÑÐ¸Ð²Ð½ÑÐ¼ Ð¿ÑÐ¸ ÑÐµÑÐµÐ½Ð¸Ð¸ Ð·Ð°Ð´Ð°ÑÐ¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð°ÐºÑÐµÐ½ÑÐ°, ÑÐµÐ¼ MFCC. ÐÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¾ÑÐ° Ñ Ð¼ÐµÐ»-ÑÐ¿ÐµÐºÑÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð°Ð¼Ð¸ Ð² ÐºÐ°ÑÐµÑÑÐ²Ðµ Ð²ÑÐ¾Ð´Ð½ÑÑ Ð¿ÑÐ¸Ð·Ð½Ð°ÐºÐ¾Ð² Ð¾ÑÐµÐ½Ð¸Ð²Ð°ÐµÑÑÑ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÐ°ÐºÐ¸Ñ Ð¼ÐµÑÑÐ¸Ðº ÐºÐ°Ðº Ð¼Ð°ÑÑÐ¸ÑÑ Ð¾ÑÐ¸Ð±Ð¾Ðº, Ð¾Ð±ÑÐ°Ñ ÑÐ¾ÑÐ½Ð¾ÑÑÑ, ÑÐ¾ÑÐ½Ð¾ÑÑÑ, Ð¿Ð¾Ð»Ð½Ð¾ÑÐ° Ð¸ F1, Ð¸ Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸ÑÑÑ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½Ð¾Ð¹ ÑÐ¾ÑÐ½Ð¾ÑÑÐ¸ Ñ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ð¼Ð¸ Ð½Ð° Ð´Ð°Ð½Ð½ÑÐ¹ Ð¼Ð¾Ð¼ÐµÐ½Ñ ÑÐµÑÐµÐ½Ð¸ÑÐ¼Ð¸ Ð² Ð¾Ð±Ð»Ð°ÑÑÐ¸.
description: The problem of accent recognition has received a lot of attention with the development of ASR systems, since conventional acoustic language models, adapted to fit the standard language corpus, do not fulfill the recognition requirements when applied to accented speech. Since neural networks of CNN architecture have proven to be effective in solving a problem of accent recognition, such a model is investigated in this thesis. The model has been trained on various audio features extracted from the Speech Accent Archive dataset. It has been experimentally shown that adding further information about audio signals to the MFCC in some cases leads to an increase in the accuracy of the accent classification. It was found that the use of linear mel-scaled spectrograms of amplitude for a dataset chosen appears more effective in accent classification problem solving than MFCC. The use of a classifier model with mel-scaled spectrograms as input features is evaluated using metrics such as confusion matrices, overall accuracy, precision, recall and F1, and the reached accuracy is compared with current solutions in the field.