Preliminary evaluation of angry voice in automatic speech recognition
نویسندگان
چکیده
Speech recognition has been introduced as an interface for the various devices; especially operator assistance in call center operations is needed. But when speech recognition is introduced into the call center operations, the recognition performance may deteriorate because the voices of customers include emotion (angry). Previous study reported that the recognition performance of “angry voice” tend to deteriorate than that of “calm voice”. The acoustic features of “angry voice” are different from those of “calm voice”, for example, loud power and high voice. In this study, to explore what factors make the recognition performance deteriorating, we record the parallel speech corpus of “calm voice” and “angry voice” in Japanese, carry out the recognition experiments. And, we compare speech pitch, speech power and spectral envelope between speaker of little deteriorating of speech recognition rate and speaker of deteriorating of speech recognition rate for five vowels. In the results, about speaker deteriorating recognition rate, speech pitch of /i/ increased (about 5dB) and speech power of /u/ increased (about 40Hz) on “angry voice” of “incorrectly words”. Particularly, it was confirmed that the spectral envelopes of /i/ and /u/ on “angry voice” were changed the form.
منابع مشابه
A Database for Automatic Persian Speech Emotion Recognition: Collection, Processing and Evaluation
Abstract Recent developments in robotics automation have motivated researchers to improve the efficiency of interactive systems by making a natural man-machine interaction. Since speech is the most popular method of communication, recognizing human emotions from speech signal becomes a challenging research topic known as Speech Emotion Recognition (SER). In this study, we propose a Persian em...
متن کاملEvaluation of Acoustic Correlates of Speech Under Stress for Robust Speech Recognition
This paper presents results from an investigation of how speech characteristics change under varying levels of stress with specific application to improving automatic isolated-word speech recognition. In JASA-87 [2], preliminary results were presented, based on a series of probe studies which served to identify possible stress relayers in a speech recognition/communication framework. This paper...
متن کاملVoice-based Age and Gender Recognition using Training Generative Sparse Model
Abstract: Gender recognition and age detection are important problems in telephone speech processing to investigate the identity of an individual using voice characteristics. In this paper a new gender and age recognition system is introduced based on generative incoherent models learned using sparse non-negative matrix factorization and atom correction post-processing method. Similar to genera...
متن کاملTwo-layered audio-visual integration in voice activity detection and automatic speech recognition for robots
Automatic Speech Recognition (ASR) which plays an important role in human-robot interaction should be noise-robust because robots are expected to work in noisy environments. Audio-Visual (AV) integration is one of the key ideas to improve the robustness in such environments. This paper proposes two-layered AV integration for ASR which applies AV integration to Voice Activity Detection (VAD) and...
متن کاملUse of Procedural Knowledge for Automatic Speech Recognition
A paradigm for automatic speech recognition using networks of actions performing variable depth analysis is presented. The paradigm produces descriptions of speech properties that are related to speech units through Markov models representing system performance. Preliminary results in the recognition of isolated letters and digits are presented. 1. I N T R O D U C T I O N Recent results on Auto...
متن کامل