Speech Recognition Method and System in Which Said Method Is Implemented

The present invention relates to a method of recognizing spoken words, according to which method words are put in a dictionary in the form of vectors, the method comprising the following steps:

breakdown of the word to be recognized into input vectors,

evaluation of ambient noise,

choice of the word to be recognized from the words of the dictionary while said noise evaluation step is taken into account, via a choice of the dictionary word of which the distance that separates its input vectors from the reference vectors is the smallest, and

validation of the word to be recognized by a comparison of said distance with a threshold value.

The invention also relates to a system in which the method is applied, notably a wireless telephony device for cellular radiophone networks for which the hardware resources, memories and processors are on the whole assigned in limited manner. Such a method is described in European patent EP 0 750 292. According to this known method, the noise is estimated and all the vectors of the input signal and the vectors of the reference signals are modified as a function of this noise level into other vectors.

This known method is not very applicable to small-size devices in which the hardware resources are limited, notably the memory. Furthermore, these updates of the reference vectors take time causing delay which is annoying to the user of small devices.

The present invention proposes a method of the type described above which provides good performance as regards the recognition of speech in a noisy environment, while only very little of the hardware resources, notably the memory is used.

Therefore, such a method of the type defined in the opening paragraph is characterized in that it comprises at least the following step:

modification of the threshold value as a function of the result of the evaluation of ambient noise.

The idea of the invention is based on the fact that when a person is in a silent environment, the recognition of speech is to take place with a low threshold, because the conditions are all right. When the environment becomes noisy, a more tolerant threshold is to be provided, because the noise degrades the input vectors.

These and other aspects of the invention will be apparent from and elucidated with reference to the embodiments described hereinafter.

In the drawings:

FIG. 1 shows a device according to the invention,

FIG. 2 shows a timing diagram,

FIG. 3 shows a flow chart explaining the method according to the invention,

FIG. 4 shows the evolution of the threshold as a function of ambient noise, and

FIG. 5 shows a flow chart explaining a variant of an embodiment of the method according to the invention.

In FIG. 1, the device in which the method may be used is a cellular telephony device of the GSM terminal type. It is formed by a transceiver assembly 5. A transceiver antenna 7 for receiving and transmitting waves from and to a base station (not shown) is connected to this assembly 5. For the user to exchange remarks with his called parties, a user interface 9 includes a microphone 10 and a loudspeaker 12. This microphone will also be used for applying speech recognition so that the user will be able to give orders and/or manage his telephone directory by calling the known name. The other elements of user interface 9 such as a screen or a keyboard are not represented because they are used little in the invention. The device shown in FIG. 1 has a microprocessor assembly 15 which comprises an actual microprocessor 17, a random-access memory 18 and a read-only memory 19 containing the instructions for implementing the method according to the invention, and an electrically erasable memory 20 for containing the reference vectors which define the vocabulary to be recognized and also to be updated. This microprocessor assembly 15 communicates its information to all the other elements of the device over a common line 25.

FIG. 2 shows a timing diagram which represents the voice signals in A.

According to the usual speech recognition techniques, such as explained in above-mentioned European patent, evolutionary spectrums are determined for these voice signals for a time .tau. represented in B in FIG. 2 by the spectral lines R1, R2 . . . . The various lines of this spectrum obtained by fast Fourier transform, for example, constitute vectors. For determining the recognition of a word, these various lines are compared with those established previously which form the dictionary and are stored in the memory 20.

FIG. 3 shows the flow chart which explains the method according to the invention.

Box K0 represents the activation of speech recognition; this may be made by validating an item on a menu which appears on the screen of the device.

Box K1 represents the step of the evaluation of ambient noise. This step is executed between the instants t0 and t1 (see FIG. 2) between which the speaker is supposed not to speak, i.e. before the speaker has spoken the word to be recognized. Supposing Nb is this value which is expressed in dB relative to the maximum level (if one works with 8 bits, this maximum level 0 dB is given by 1111 1111). This measure is taken considering the mean value of the noise vectors, their moduli, or their squares. From this level measured in this manner is derived a threshold TH (box K2) as a function of the curve shown in FIG. 4.

Box K2a represents the breakdown of a spoken word to be recognized into input vectors V.sub.i.

Box K3 indicates the computation of the distances d.sup.k between the input vectors V.sub.i and the reference vectors w.sup.K.sub.i. This distance is evaluated based on the absolute value of the differences between the components of these vectors. In box K4 is determined the minimum distance D.sup.B among the minimum distances which have been computed. This minimum value is compared with the threshold value TH, box K5. If this value is higher than the threshold TH, the word is rejected in box K6, if not, it is declared recognized in box K7.

The order of various steps may be reversed in the method according to the invention. As this is shown in FIG. 5, the evaluation of the ambient noise may also be carried out after the speaker has spoken the word to be recognized, that is, between the instants t0' and t1' (see FIG. 2). This is translated in the flow chart of FIG. 5 by the fact that the steps K1 and K2 occur after step K4 and before decision step K5.

The end of this ambient noise evaluation step, according to a characteristic feature of the invention, may be signaled to the speaker in that a beep is emitted, for example, by a loudspeaker 12 which then invites the speaker to speak.

The applicants have taken into account that a substantially linear function of the threshold value as a function of the measured noise level in dB was satisfactory. Other functions may be found too, without leaving the scope of the invention therefore.

If the distances vary between a value from 0 to 100, the values of TH1 may be 10 and those of TH2 80 for noise levels varying from -25 dB to -5 dB.

For the computation of the threshold TH, the noise level (Nb) may be compared with the signal level (Ns) which defines a signal-to-noise ratio SNR (computed signal level based on input vectors: V.sub.i). ##EQU1## where B.sub.i are noise components. SNR (signal-to-noise ratio=Ns/Nb.

The curve giving TH plotted against SNR is the same as TH plotted against Nb.

Also, within the scope of the invention, it is possible to evaluate the noise when the user is speaking, by utilizing autocorrelation methods.

In that case, Nb and Ns are computed on the same step level and TH is evaluated on the basis of SNR.