Sentence examples for approaches for speech from inspiring English sources

In this study, two new approaches for speech signal noise reduction based on the empirical mode decomposition (EMD) recently introduced by Huang et al. (1998) are proposed.

This work assesses different approaches for speech and non-speech segmentation of audio data and proposes a new, high-level representation of audio signals based on phoneme recognition features suitable for speech/non-speech discrimination tasks.

When two different approaches for speech intervention in children with cleft palate and CA were compared phonetic versus phonologic the total time of speech intervention necessary for correcting CA was critically reduced when a phonological approach was used [ 27].

In this study, we propose an approach for speech classification based on spectrogram images.

In this work, we investigated a different approach for speech dereverberation that is based on learning from data.

We evaluate the DNN approach for speech enhancement and compare it to the approach of DS beamformer plus spectral subtraction (SS).

Inverse filtering of room transfer functions (RTFs) is considered an attractive approach for speech dereverberation given that the time invariance assumption of the used RTFs holds.

In this paper, we propose an approach for speech classification using Scale-invariant Feature Transform (SIFT) features on spectrogram images of speech signal combination with Local naïve Bayes nearest neighbor.

The most similar approach to that described can be found in [26] where an HMM model is used together with a concatenation approach for speech synthesis of both audio and visual parameters.

Standard objective measures as well as subjective evaluations show that the proposed method is capable of outperforming the existing state-of-the-art thresholding-based speech enhancement approaches for noisy speech of high as well as low levels of SNR.

Thus, the underlying pedagogy for each profession appears to be the driver behind approaches selected for speech work, with the occupational therapists focusing more on the oral musculature and the teachers more on the behavioural aspects of speech and language.