Labeling speech events for acoustic and linguistic processing
نویسندگان
چکیده
منابع مشابه
Acoustic and Linguistic Characterization of Spontaneous Speech
Although speech derived from reading texts, and similar types of speech, e.g. that from reading newspapers or that from news broadcast, can be recognized with high accuracy, recognition accuracy drastically decreases for spontaneous speech. This is due to the fact that spontaneous speech and read speech are significantly different acoustically as well as linguistically. This paper reports analy...
متن کاملFusion of Acoustic and Linguistic Speech Features for Emotion Detection
This paper describes a system that deploys acoustic and linguistic information from speech in order to decide whether the utterance contains negative or nonnegative meaning. An earlier version of this system was submitted to the Interspeech-2009 Emotion Challenge evaluation. The speech data consist of short utterances of the children’s speech, and the proposed system is designed to detect anger...
متن کاملProsody recognition from speech utterances using acoustic and linguistic based models of prosodic events
A system for automatic recognition of prosodic events in speech utterances has been developed and applied to recognizing accent tones as de ned by the tone and break index (ToBI) prosodic labeling standard. Both the acoustic and syntactic modeling portions of the system are described in the paper. The acoustic modeling portion of the system involves representation of ToBI labeled events using h...
متن کاملSpeech Emotion Recognition Exploiting Acoustic and Linguistic Information Sources
A variety of approaches towards Speech Emotion Recognition were presented since the research activities started in the late last decade. Today we are all aware of the great importance of emotional aspects as the next step towards more natural human-machine interaction. Yet, a growing number of isolated individual groups contribute to the general advances in the exciting landscape we see today. ...
متن کاملAnger recognition in speech using acoustic and linguistic cues
The present study elaborates on the exploitation of both linguistic and acoustic feature modeling for anger classification. In terms of acoustic modeling we generate statistics from acoustic audio descriptors, e.g. pitch, loudness, spectral characteristics. Ranking our features we see that loudness and MFCC seems most promising for all databases. For the English database also pitch features are...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal of the Acoustical Society of America
سال: 1976
ISSN: 0001-4966
DOI: 10.1121/1.2003180