Sentence examples for sum of speech from inspiring English sources

If s(n) and w(n) are statistically independent, then the energy of x(n) is the sum of speech and noise energies: E x  = E s  + E w.

The total misclassification errors (sum of speech detection error and non-speech detection error) for all combinations of M (1, 5, 10, 20, 30, and 40) and R (5, 10, 20, 30, and 40) are computed over 12 types of noise for five SNR levels (−10, −5, 0, 5, and 10 dB).

With the G-MWF, the speech reference is a weighted sum of the speech components, such that the output signal has the same phase as the speech component in the reference microphone.

We calculated the total misclassification error which is the sum of the speech detection error and non-speech detection error.

At ADF input, and are the powers of the clean mixture and the noise components, respectively; and are the powers of the target and the interference speech signals, respectively; is the sum of interference speech and noise.

In [7], the generalized MWF was presented, where the elements u i of the vector u define a speech reference for the MWF which is a weighted sum of the speech components in the different microphones with the phase of the speech component in the reference microphone signal.

The gross bit rate is the sum of the speech codec bit rate and the channel codec[8].

Only the direct path of the two sources was simulated, whereas the reverberation was simulated as a diffuse noise field that was shaped by the temporal envelope of the sum of both speech sources and added with an SDR of 10 dB.

The a priori knowledge about the speech includes the following autoregressive model [14]: The current speech sample s(n) is assumed to be a sum of the predicted speech s +(n) and the prediction error e(n) (cf. Figure 1), the latter being a zero-mean (random) signal which is statistically independent of s +(n).

As m x is a model for the speech PSD and m w is a model for the noise PSD, m=[m x,m w ] is a model for the noisy PSD, given by the sum of the corresponding speech and noise PSDs.

The final score is the sum of the Responsiveness, Speech, Facial expression, and Eyes component scores.