The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
An auditory-based feature extraction algorithm is proposed for enhancing the robustness of automatic speech recognition. In the proposed approach, the speech signal is characterized using a new feature referred to as the Basilar-membrane Frequency-band Cepstral Coefficient (BFCC). In contrast to the conventional Mel-Frequency Cepstral Coefficient (MFCC) method based on a Fourier spectrogram, the proposed...
A novel BInaural Spectro-Temporal (BIST) algorithm is proposed in this paper to increase the speech intelligibility in low or negative SNR noisy environments. The BIST algorithm consists of two modules. One is the spatial mask for receiving sound from the specific direction, and the other is the spectro-temporal modulation filter for noise reduction. Most speech enhancement algorithms are not applicable...
This paper presented a robust sound recognition work applied to awareness for health/children/elderly care. Specific sound awareness services can be activated based on recognized sound classes for detecting human activities as health care. To attain this goal, this study developed key technologies as follows: 1) SNR-aware subspace signal enhancement, 2) pitch and power density-based sound/speech discrimination,...
In this study, we introduce a noisy environment-aware speech enhancement system, which can be used in human-robot interaction (HRI) application for command recognition. In order to effectively filter different noises and improve speech recognition rates, the proposed system adopts automatic noise cancellation that is combined with independent component analysis (ICA) and subspace speech enhancement...
In this paper, we propose a design of far-field single speaker localization system including noisy speech separation and enhancement with two separated channel microphones. First, we perform noisy speech separation simulations using a fast-ICA (independent component analysis) with subspace-based speech enhancement. The fast-ICA can be used to separate the two original source signals-noise and speech...
This paper proposes a new noise estimation algorithm to reduce the estimation delays under highly non-stationary noise conditions. Since the harmonic ripples appeared in the spectrogram are valuable for human to localize the speech presence, based on the characteristics of these ripples, we propose a novel energy independent feature to detect the changing noise. If noise is present, the noise floors...
While many efforts have been made in the audio signal classification field, the noise interruption problem is seldom concerned so far, especially in many telecommunication applications, where a real-time and noise robust approach is needed. This paper addresses this problem by proposing two novel robust features: average pitch density (APD) and relative tonal power density (RTPD). APD refers to the...
In this paper, a new subspace-based speech enhancement model is presented for in-car speech enhancement. To effectively suppress background noise, this model incorporates a perceptual filterbank and an auditory gain adaptation derived from a psychoacoustic model into a signal subspace approach. The projection approximation subspace tracking deflation (PASTd) algorithm is used to track the signal subspace...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.