Zobrazeno 1 - 4
of 4
pro vyhledávání: '"V. V. Vidyadhara Raju"'
Publikováno v:
INTERSPEECH
With the growing popularity of social networks, cloud services and online applications, people are becoming concerned about the way companies store their data and the ways in which the data can be applied. Privacy with devices and services operated b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fc32dc1f8c72a5e4b6a6263553783e6
https://doi.org/10.21437/interspeech.2019-1172
https://doi.org/10.21437/interspeech.2019-1172
Publikováno v:
APSIPA
A mismatch in training and operating environments causes a performance degradation in speech recognition systems (ASR). One major reason for this mismatch is due to the presence of expressive (emotive) speech in operational environments. Emotions in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae13c9a14d68976ec4b3f43b4d7ae3a8
https://doi.org/10.1109/apsipa.2017.8282109
https://doi.org/10.1109/apsipa.2017.8282109
Autor:
Anil Kumar Vuppala, V. V. Vidyadhara Raju, K. N. R. K. Raju Alluri, Suryakanth V. Gangashetty
Publikováno v:
2016 IEEE Region 10 Conference (TENCON).
Source and system features are extensively used in building Speaker Recognition (SR) systems. In this paper, we investigate the influence of source and system features on the performance of the SR system in emotional conditions. The Linear Prediction
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa405c0c374100f21ecc3d69d6797c83
https://doi.org/10.1109/tencon.2016.7848563
https://doi.org/10.1109/tencon.2016.7848563
Publikováno v:
2016 IEEE Region 10 Conference (TENCON).
The main focus of this study is to analyze the performance of Automatic Speech Recognition (ASR) in different emotional environments using prosody modification. The majority of ASR systems are trained using neutral speech and the performance of such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8bf5a56f765ad2cc7a7d308e12e80bb1
https://doi.org/10.1109/tencon.2016.7848145
https://doi.org/10.1109/tencon.2016.7848145