Does it Groove or does it Stumble - Automatic Classification of Alcoholic Intoxication using Prosodic Features
نویسندگان
چکیده
This paper studies how prosodic features can help in the automatic detection of alcoholic intoxication. We compute features that have recently been proposed to model speech rhythm such as the pair-wise variability index for consonantal and vocalic segments (PVI) and study their aptness for the task. Further, we use a large prosodic feature vector modelling the usual candidates – pitch, intensity, and duration – and apply it onto different units such as words, syllables and stressed syllables to create generalizations of the rhythm features mentioned. The results show that the prosodic features computed are suitable for detecting alcoholic intoxication and add complementary information to state-of-the-art features. The database is the intoxication database provided by the organizers of the 2011 Interspeech Speaker State Challenge.
منابع مشابه
Automatic classification of Non-alcoholic fatty liver using texture features from ultrasound images
Background: Accurate and early detection of non-alcoholic fatty liver, which is a major cause of chronic diseases is very important and is vital to prevent the complications associated with this disease. Ultrasound of the liver is the most common and widely performed method of diagnosing fatty liver. However, due to the low quality of ultrasound images, the need for an automatic and intelligent...
متن کاملUse of prosodic speech characteristics for automated detection of alcohol intoxication
In this paper we describe our methodology for automatic detection of speaker alcoholization. Our task is restricted to detection of considerable alcoholization (alcohol blood level ≥ 0.8 per mille), so that a two-class classification problem is to be solved. In particular, our attention is focused on the influence of the alcohol intoxication on the prosodical aspect of the spoken language. A ne...
متن کاملAutomatic prosodic prominence detection in speech using acoustic features: an unsupervised system
This paper presents work in progress on the automatic detection of prosodic prominence in continuous speech. Prosodic prominence involves two different phonetic features: pitch accents, connected with fundamental frequency (F0) movements and syllable overall energy, and stress, which exhibits a strong correlation with syllable nuclei duration and mid-to-high-frequency emphasis. By measuring the...
متن کاملAutomatic detection of speaker state: Lexical, prosodic, and phonetic approaches to level-of-interest and intoxication classification
Traditional studies of speaker state focus primarily upon one-stage classification techniques using standard acoustic features. In this article, we investigate multiple novel features and approaches to two recent tasks in speaker state detection: level-of-interest (LOI) detection and intoxication detection. In the task of LOI prediction, we propose a novel Discriminative TFIDF feature to captur...
متن کاملPerception of Alcoholic Intoxication in Speech
The ALC sub-challenge of the Interspeech Speaker State Challenge (ISSC) aims at the automatic classification of speech signals into intoxicated and sober speech. In this context we conducted a perception experiment on data derived from the same corpus to analyze the human performance on the same task. The results show that human still outperform comparable baseline results of ISSC. Female and m...
متن کامل