Sentence examples for frame of speech from inspiring English sources

A pre-emphasis filter with a factor of 0.97 is applied to each frame of speech.

Figure 1 depicts the multi-taper spectrum estimation process from a frame of speech signal with M = 6 orthogonal tapers.

We choose the template unit to be context-dependent phone segments (triphone context) and use multiple Gaussian mixture model (GMM) indices to represent each frame of speech templates.

Each frame of speech data was converted into a sequence of 39 dimensional feature vectors of 12 MFCCs augmented with log energy, their first and second derivatives.

For every training frame of speech t, entry ( m ^ t, k ^ t ) of the association matrix Φ (as shown in Figure 2) is incremented by 1.

Let S k (n), N k (n), Z k (n) denote the k th spectral component of the n th frame of speech, noise and observed signal, respectively.

Mel frequency cepstral coefficients (MFCCs) are extracted on 10 milliseconds spaced frames of speech samples.

This method is based on the concept of transforming/replacing short frames of speech synthesized by HMMSS to the physically closest frames of the original speech.

We test over 20,000 frames of speech coming from several speakers with unlike characteristics (gender, age, pitch, regional accent).

An important shortcoming is the shrinkage of the unvoiced frames of speech which contain many noise-like speech components leading to a degraded speech quality.

In the linear feature adaptation approach, a sparse linear transform, called cross transform, is used to transform multiple frames of speech coefficients to a new feature space.