Add to ORKGFrequency Domain Linear Prediction (FDLP) provides an efficient way to represent temporal envelopes of a signal using auto-regressive models. For the input speech signal, we use FDLP to estimate temporal trajectories of sub-band energy by applying linear prediction on the cosine transform of sub-band signals. The sub-band FDLP envelopes are used to extract spectral and temporal features for speech recognition. The spectral features are derived by integrating the temporal envelopes in short-term frames and the temporal features are formed by converting these envelopes into modulation frequency components. These features are then combined in the phoneme posterior level and used as the input features for a hybrid HMM-ANN based phoneme recogniz...
In this paper we present first experimental results with a novel audio coding technique based on app...
The temporal trajectories of the spectral energy in auditory critical bands over 250 ms segments are...
Frequency Domain Linear Prediction (FDLP) represents an effi-cient technique for representing the lo...
We present a new feature extraction technique for phoneme recognition that uses short-term spectral ...
In this paper, we present a spectro-temporal feature extraction technique using sub-band Hilbert env...
Current speech recognition systems uniformly employ short-time spectral analysis, usually over windo...
Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 200
Autoregressive modeling is applied for approximating the temporal evolution of spectral density in c...
Frequency domain linear prediction (FDLP) is a technique for auto-regressive (AR) modeling of Hilber...
Performance of a typical automatic speech recognition (ASR) system severely degrades when it encount...
In this paper, a new feature extraction technique based on modulation spectrum derived from syllable...
The speech signal is inherently characterized by its variations in time, which get reflected as vari...
Recognition of reverberant speech constitutes a challenging problem for typical speech recognition s...
Overview of Frequency-Domain Linear Prediction (FDLP) as a novel approach to speech recognition
Feature extraction of speech signals is typically performed in short-time frames by assuming that th...
In this paper we present first experimental results with a novel audio coding technique based on app...
The temporal trajectories of the spectral energy in auditory critical bands over 250 ms segments are...
Frequency Domain Linear Prediction (FDLP) represents an effi-cient technique for representing the lo...
We present a new feature extraction technique for phoneme recognition that uses short-term spectral ...
In this paper, we present a spectro-temporal feature extraction technique using sub-band Hilbert env...
Current speech recognition systems uniformly employ short-time spectral analysis, usually over windo...
Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 200
Autoregressive modeling is applied for approximating the temporal evolution of spectral density in c...
Frequency domain linear prediction (FDLP) is a technique for auto-regressive (AR) modeling of Hilber...
Performance of a typical automatic speech recognition (ASR) system severely degrades when it encount...
In this paper, a new feature extraction technique based on modulation spectrum derived from syllable...
The speech signal is inherently characterized by its variations in time, which get reflected as vari...
Recognition of reverberant speech constitutes a challenging problem for typical speech recognition s...
Overview of Frequency-Domain Linear Prediction (FDLP) as a novel approach to speech recognition
Feature extraction of speech signals is typically performed in short-time frames by assuming that th...
In this paper we present first experimental results with a novel audio coding technique based on app...
The temporal trajectories of the spectral energy in auditory critical bands over 250 ms segments are...
Frequency Domain Linear Prediction (FDLP) represents an effi-cient technique for representing the lo...