Recognition of emotions in Mexican Spanish speech: an approach based on acoustic modelling of emotion-specific vowels.
An approach for the recognition of emotions in speech is presented. The target language is Mexican Spanish, and for this purpose a speech database was created. The approach consists in the phoneme acoustic modelling of emotion-specific vowels. For this, a standard phoneme-based Automatic Speech Recognition (ASR) system was built with Hidden Markov Models (HMMs), where different phoneme HMMs were built for the consonants and emotion-specific vowels associated with four emotional states (anger, happiness, neutral, sadness). Then, estimation of the emotional state from a spoken sentence is performed by counting the number of emotion-specific vowels found in the ASR's output for the sentence. With this approach, accuracy of 87-100% was achieved for the recognition of emotional state of Mexican Spanish speech.
Technological University of the Mixteca, Huajuapan de León, OAX, Mexico. scaballero@mixteco.utm.mx
Santiago-Omar
SO
Caballero-Morales
D000162:Acoustics; D004644:Emotions; D006801:Humans; D008800:Mexico; D008962:Models, Theoretical; D013030:Spain; D013060:Speech