Getting started with SUSAS: a speech under simulated and actual stress database
نویسندگان
چکیده
It is well known that the introduction of acoustic background distortion and the variability resulting from environmentally induced stress causes speech recognition algorithms to fail. In this paper, we discuss SUSAS: a speech database collected for analysis and algorithm formulation of speech recognition in noise and stress. The SUSAS database refers to Speech Under Simulated and Actual Stress, and is intended to be employed in the study of how speech production and recognition varies when speaking during stressed conditions. This paper will discuss (i) the formulation of the SUSAS database, (ii) baseline speech recognition using SUSAS data, and (iii) previous research studies which have used the SUSAS data base. The motivation for this paper is to familiarize the speech community with SUSAS, which was released April 1997 on CD-ROM through the NATO RSG.10.
منابع مشابه
Multistyle classification of speech under stress using feature subset selection based on genetic algorithms
The determination of an emotional state through speech increases the amount of information associated with a speaker. It is therefore important to be able to detect and identify a speaker's emotional state or state of stress. Various techniques are used in the literature to classify emotional/stressed states on the basis of speech, often using di erent speech feature vectors at the same time. T...
متن کاملSpeaker Identification in the Shouted Environment Using Suprasegmental Hidden Markov Models
In this paper, Suprasegmental Hidden Markov Models (SPHMMs) have been used to enhance the recognition performance of text-dependent speaker identification in the shouted environment. Our speech database consists of two databases: our collected database and the Speech Under Simulated and Actual Stress (SUSAS) database. Our results show that SPHMMs significantly enhance speaker identification per...
متن کاملSpeech feature modeling for robust stressed speech recognition
It is well known that the performance of speech recognition algorithms degrade in the presence of adverse environments where a speaker is under stress, emotion, or Lombard e ect. This study evaluates the e ectiveness of traditional features in recognition of speech under stress and formulates new features which are shown to improve stressed speech recognition. The focus is on formulating robust...
متن کاملA comparative study of traditional and newly proposed features for recognition of speech under stress
It is well known that the performance of speech recognition algorithms degrade in the presence of adverse environments where a speaker is under stress, emotion, or Lombard effect. This study evaluates the effectiveness of traditional features in recognition of speech under stress and formulates new features which are shown to improve stressed speech recognition. The focus is on formulating robu...
متن کاملAnchor Model Fusion for Emotion Recognition in Speech
In this work, a novel method for system fusion in emotion recognition for speech is presented. The proposed approach, namely Anchor Model Fusion (AMF), exploits the characteristic behaviour of the scores of a speech utterance among different emotion models, by a mapping to a back-end anchor-model feature space followed by a SVM classifier. Experiments are presented in three different databases:...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1997