Model Compensation Approach Based on Nonuniform Spectral Compression Features for Noisy Speech Recognition
نویسندگان
چکیده
منابع مشابه
Model Compensation Approach Based on Nonuniform Spectral Compression Features for Noisy Speech Recognition
This paper presents a novel model compensation (MC) method for the features of mel-frequency cepstral coefficients (MFCCs) with signal-to-noise-ratio(SNR-) dependent nonuniform spectral compression (SNSC). Though these newMFCCs derived from a SNSC scheme have been shown to be robust features under matched case, they suffer from serious mismatch when the reference models are trained at different...
متن کاملFeature extraction and model-based noise compensation for noisy speech recognition evaluated on AURORA 2 task
We have evaluated several feature-based and a model-based method for robust speech recognition in noise. The evaluation was performed on Aurora 2 task. We show that after a subband based spectral subtraction, features can be more robust to additive noise. We also report a robust feature set derived from differential power spectrum (DPS), which is not only robust to additive noise, but also robu...
متن کاملSpeech Emotion Recognition Based on Power Normalized Cepstral Coefficients in Noisy Conditions
Automatic recognition of speech emotional states in noisy conditions has become an important research topic in the emotional speech recognition area, in recent years. This paper considers the recognition of emotional states via speech in real environments. For this task, we employ the power normalized cepstral coefficients (PNCC) in a speech emotion recognition system. We investigate its perfor...
متن کاملRobust Speech Recognition Features Based on Temporal Trajectory Filtering and Non-Uniform Spectral Compression
This paper proposes a new feature extraction method based on temporal trajectory filtering and nonuniform spectral compression and examines its performance with two tasks in noisy environments. Temporal trajectory filtering is effective for robust speech recognition in noisy environments, due to human hearing is more sensitive to relative values rather than absolute values and the effect of add...
متن کاملFeature compensation technique for robust speech recognition in noisy environments
In this paper, we analyze the problems of the existing interacting multiple model (IMM) and spectral subtraction (SS) approaches and propose a new approach to overcome the problems of these algorithms. Our approach combines the IMM and SS techniques based on a soft decision for speech presence. Results reported on AURORA2 database show that proposed approach shows 14.26 % of average relative im...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2007
ISSN: 1687-6180
DOI: 10.1155/2007/32546