Enhancing Multilingual Recognition of Emotion in Speech by Language Identification
نویسندگان
چکیده
We investigate, for the first time, if applying model selection based on automatic language identification (LID) can improve multilingual recognition of emotion in speech. Six emotional speech corpora from three language families (Germanic, Romance, Sino-Tibetan) are evaluated. The emotions are represented by the quadrants in the arousal/valence plane, i. e., positive/negative arousal/valence. Four selection approaches for choosing an optimal training set depending on the current language are compared: within the same language family, across language family, use of all available corpora, and selection based on the automatic LID. We found that, on average, the proposed LID approach for selecting training corpora is superior to using all the available corpora when the spoken language is not known.
منابع مشابه
Statistical Variation Analysis of Formant and Pitch Frequencies in Anger and Happiness Emotional Sentences in Farsi Language
Setup of an emotion recognition or emotional speech recognition system is directly related to how emotion changes the speech features. In this research, the influence of emotion on the anger and happiness was evaluated and the results were compared with the neutral speech. So the pitch frequency and the first three formant frequencies were used. The experimental results showed that there are lo...
متن کاملCross-lingual and Multilingual Speech Emotion Recognition on English and French
Research on multilingual speech emotion recognition faces the problem that most available speech corpora differ from each other in important ways, such as annotation methods or interaction scenarios. These inconsistencies complicate building a multilingual system. We present results for crosslingual and multilingual emotion recognition on English and French speech data with similar characterist...
متن کاملMultilingual Speech Emotion Recognition System Based on a Three-Layer Model
Speech Emotion Recognition (SER) systems currently are focusing on classifying emotions on each single language. Since optimal acoustic sets are strongly language dependent, to achieve a generalized SER system working for multiple languages, issues of selection of common features and retraining are still challenging. In this paper, we therefore present a SER system in a multilingual scenario fr...
متن کاملLanguage Identification and Multilingual Speech Recognition Using Discriminatively Trained Acoustic Models
We perform language identification experiments for four prominent South-African languages using a multilingual speech recognition system. Specifically, we show how successfully Afrikaans, English, Xhosa and Zulu may be identified using a single set of HMMs and a single recognition pass. We further demonstrate the effect of language identification-specific discriminative acoustic model training ...
متن کاملMultilingual Speech Recogn Identificat
This paper presents a new approach to multilingual speech recognition. The proposed algorithm combines both language identification (LID) and speech recognition into a single process. It is shown to be effective for multilingual grammarbased speech recognition where the language information is not available prior to recognition. The idea is to make use of acoustic-phonetic and lexical informati...
متن کامل