EP1143412A1 - Estimating the pitch of a speech signal using an intermediate binary signal - Google Patents
Estimating the pitch of a speech signal using an intermediate binary signal Download PDFInfo
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- EP1143412A1 EP1143412A1 EP00610034A EP00610034A EP1143412A1 EP 1143412 A1 EP1143412 A1 EP 1143412A1 EP 00610034 A EP00610034 A EP 00610034A EP 00610034 A EP00610034 A EP 00610034A EP 1143412 A1 EP1143412 A1 EP 1143412A1
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- signal
- pitch
- speech
- speech signal
- autocorrelation
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- 238000000034 method Methods 0.000 claims abstract description 24
- 238000005070 sampling Methods 0.000 claims abstract description 8
- 238000001914 filtration Methods 0.000 claims description 9
- 238000005311 autocorrelation function Methods 0.000 description 12
- 238000001514 detection method Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 230000005284 excitation Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000001755 vocal effect Effects 0.000 description 2
- 230000001419 dependent effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 210000004072 lung Anatomy 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 210000001260 vocal cord Anatomy 0.000 description 1
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/90—Pitch determination of speech signals
Definitions
- the intermediate signal may be provided by calculating the autocorrelation of a signal derived from the speech signal by filtering the speech signal through a filter based on a set of filter parameters estimated by means of linear predictive analysis (LPA).
- LPA linear predictive analysis
- the best estimate is achieved when the device is adapted to select the sample having the maximum amplitude of said conformity function as the estimate of the pitch.
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- Engineering & Computer Science (AREA)
- Computational Linguistics (AREA)
- Signal Processing (AREA)
- Health & Medical Sciences (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- Acoustics & Sound (AREA)
- Multimedia (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
A method of estimating the pitch of a speech signal (2)
comprises the steps of sampling the speech signal to obtain
a series of samples, dividing the series of samples
into segments, each segment having a fixed number of consecutive
samples, calculating for each segment a conformity
function, and detecting peaks in the conformity
function. The method further comprises the steps of providing
an intermediate signal derived from the speech
signal, converting the intermediate signal to a binary
signal, which is set to logical "1" where the intermediate
signal exceeds a pre-selected threshold and to logical
"0" where the intermediate signal does not exceed the
pre-selected threshold, calculating the autocorrelation
of the binary signal, and using the distance between
peaks in the autocorrelation of the binary signal as an
estimate of the pitch. The large amount of operations
needed in prior art algorithms is thus avoided. A similar
device is also provided.
Description
The invention relates to a method of estimating the pitch
of a speech signal, said method being of the type where
the speech signal is divided into segments, a conformity
function for the signal is calculated for each segment,
and peaks in the conformity function are detected. The
invention also relates to the use of the method in a mobile
telephone. Further, the invention relates to a device
adapted to estimate the pitch of a speech signal.
In many speech processing systems it is desirable to know
the pitch period of the speech. As an example, several
speech enhancement algorithms are dependent on having a
correct estimate of the pitch period. One field of application
where speech processing algorithms are widely used
is in mobile telephones.
A well known way of estimating the pitch period is to use
the autocorrelation function, or a similar conformity
function, on the speech signal. An example of such a
method is described in the article D. A. Krubsack, R. J.
Niederjohn, "An Autocorrelation Pitch Detector and Voicing
Decision with Confidence Measures Developed for
Noise-Corrupted Speech", IEEE Transactions on Signal
Processing, vol. 39, no. 2, pp. 319-329, Febr. 1991. The
speech signal is divided into segments of 51.2 ms, and
the standard short-time autocorrelation function is calculated
for each successive speech segment. A peak picking
algorithm is applied to the autocorrelation function
of each segment. This algorithm starts by choosing the
maximum peak (largest value) in the pitch range of 50 to
333 Hz. The period corresponding to this peak is selected
as an estimate of the pitch period.
However, such a basic pitch estimation algorithm is not
sufficient. In some cases pitch doubling can occur, i.e.
the highest peak appears at twice the pitch period. The
highest peak may also appear at another multiple of the
true pitch period. In these cases a simple selection of
the maximum peak will provide a wrong estimate of the
pitch period.
The above-mentioned article also discloses a method of
improving the algorithm in these situations. The algorithm
checks for peaks at one-half, one-third, one-fourth,
one-fifth, and one-sixth of the first estimate of
the pitch period. If the half of the first estimate is
within the pitch range, the maximum value of the autocorrelation
within an interval around this half value is located.
If this new peak is greater than one-half of the
old peak, the new corresponding value replaces the old
estimate, thus providing a new estimate which is presumably
corrected for the possibility of the pitch period
doubling error. This test is performed again to check for
double doubling errors (fourfold errors). If this most
recent test fails, a similar test is performed for tripling
errors of this new estimate. This test checks for
pitch period errors of sixfold. If the original test
failed, the original estimate is tested (in a similar
manner) for tripling errors and errors of fivefold. The
final value is used to calculate the pitch estimate.
However, this known algorithm is rather complex and requires
a high number of calculations, and these drawbacks
make it less usable in real time environments on small
digital signal processors as they are used in mobile
telephones and similar devices.
Thus, it is an object of the invention to provide a
method of the above-mentioned type which is less complex
than the prior art methods, such that the method is suitable
for small digital signal processors.
According to the invention, this object is achieved in
that the method further comprises the steps of providing
an intermediate signal derived from the speech signal,
converting the intermediate signal to a binary signal,
which is set to logical "1" where the intermediate signal
exceeds a pre-selected threshold and to logical "0" where
the intermediate signal does not exceed the pre-selected
threshold, calculating the autocorrelation of the binary
signal, and using the distance between peaks in the autocorrelation
of the binary signal as an estimate of the
pitch.
The calculation of the autocorrelation of the binary signal
takes only a fraction of the computational resources
needed for the prior art algorithms. Since there are only
values in some positions of the binary signal, the values
of the resulting autocorrelation will occur around zero
and around the pitch period of the speech signal, and
there will only be a few values separated from zero.
Thus, the pitch period can easily be estimated to the
distance between the values at position zero and the values
separated from zero. The large amount of operations
needed in prior art algorithms where a specific value has
to be found in a vector of numbers is thus avoided.
In one embodiment the intermediate signal may be provided
by filtering the speech signal through a filter based on
a set of filter parameters estimated by means of linear
predictive analysis (LPA). In this way much of the smearing
of the original speech signal is removed.
Alternatively, the intermediate signal may be provided by
calculating the autocorrelation of a signal derived from
the speech signal by filtering the speech signal through
a filter based on a set of filter parameters estimated by
means of linear predictive analysis (LPA). This solution
also removes most of the smearing of the original speech
signal, and further the possibility of clearer peaks in
the intermediate signal is improved.
If the peak corresponding to the distance between the
peaks is represented by a number of samples, the best estimate
is achieved when the sample having the maximum amplitude
of said conformity function is selected as the
estimate of the pitch.
In an expedient embodiment of the invention the method is
used in a mobile telephone, which is a typical example of
a device having only limited computational resources.
As mentioned, the invention further relates to a device
adapted to estimate the pitch of a speech signal. The device
comprises means for sampling the speech signal to
obtain a series of samples, means for dividing the series
of samples into segments, each segment having a fixed
number of consecutive samples, means for calculating for
each segment a conformity function for the signal, and
means for detecting peaks in the conformity function.
When the device further comprises means for providing an
intermediate signal derived from the speech signal, means
for converting said intermediate signal to a binary signal,
said binary signal being set to logical "1" where
the intermediate signal exceeds a pre-selected threshold
and to logical "0" where the intermediate signal does not
exceed the pre-selected threshold, means for calculating
the autocorrelation of the binary signal, and means for
using the distance between peaks in the autocorrelation
of the binary signal as an estimate of the pitch, a device
less complex than prior art devices is achieved,
which also avoids the pitch halving situation.
In one embodiment the device may be adapted to provide
the intermediate signal by filtering the speech signal
through a filter based on a set of filter parameters estimated
by means of linear predictive analysis (LPA). In
this way much of the smearing of the original speech signal
is removed.
Alternatively, the device may be adapted to provide the
intermediate signal by calculating the autocorrelation of
a signal derived from the speech signal by filtering the
speech signal through a filter based on a set of filter
parameters estimated by means of linear predictive analysis
(LPA). This solution also removes most of the smearing
of the original speech signal, and further the possibility
of clearer peaks in the intermediate signal is improved.
If the peak corresponding to the distance between the
peaks is represented by a number of samples, the best estimate
is achieved when the device is adapted to select
the sample having the maximum amplitude of said conformity
function as the estimate of the pitch.
In an expedient embodiment of the invention, the device
is a mobile telephone, which is a typical example of a
device having only limited computational resources.
In another embodiment the device is an integrated circuit
which can be used in different types of equipment.
The invention will now be described more fully below with
reference to the drawing, in which
Figure 1 shows a block diagram of an example of a pitch
detector 1 according to the invention. A speech signal 2
is sampled with a sampling rate of 8 kHz in the sampling
circuit 3 and the samples are divided into segments or
frames of 160 consecutive samples. Thus, each segment
corresponds to 20 ms of the speech signal. This is the
sampling and segmentation normally used for the speech
processing in a standard mobile telephone.
Each segment of 160 samples is then processed in a filter
4, which will be described in further detail below.
First, however, the nature of speech signals will be mentioned
briefly. In a classical approach a speech signal
is modelled as an output of a slowly time-varying linear
filter. The filter is either excited by a quasi-periodic
sequence of pulses or random noise depending on whether a
voiced or an unvoiced sound is to be created. The pulse
train which creates voiced sounds is produced by pressing
air out of the lungs through the vibrating vocal cords.
The period of time between the pulses is called the pitch
period and is of great importance for the singularity of
the speech. On the other hand, unvoiced sounds are generated
by forming a constriction in the vocal tract and
produce turbulence by forcing air through the constriction
at a high velocity. This description deals with the
detection of the pitch period of voiced sounds, and thus
unvoiced sounds will not be further considered.
As speech is a varying signal also the filter has to be
time-varying. However, the properties of a speech signal
change relatively slowly with time. It is reasonable to
believe that the general properties of speech remain
fixed for periods of 10-20 ms. This has led to the basic
principle that if short segments of the speech signal are
considered, each segment can effectively be modelled as
having been generated by exciting a linear time-invariant
system during that period of time. The effect of the filter
can be seen as caused by the vocal tract, the tongue,
the mouth and the lips.
As mentioned, voiced speech can be interpreted as the
output signal from a linear filter driven by an excitation
signal. This is shown in the upper part of figure 2
in which the pulse train 21 is processed by the filter 22
to produce the voiced speech signal 23. A good signal for
the detection of the pitch period is obtained if the excitation
signal can be extracted from the speech. By estimating
the filter parameters A in the block 24 and then
filtering the speech through an inverse filter 25 based
on the estimated filter parameters, a signal 26 similar
to the excitation signal can be obtained. This signal is
called the residual signal. This process is shown in the
lower part of figure 2. The blocks 24 and 25 are included
in the filter 4 in figure 1.
The estimation of the filter parameters is based on an
all-pole modelling which is performed by means of the
method called linear predictive analysis (LPA). The name
comes from the fact that the method is equivalent with
linear prediction. This method is well known in the art
and will not be described in further detail here.
The estimation of the pitch is based on the autocorrelation
of the residual signal, which is obtained as described
above. Thus, the output signal from the filter 4
is taken to an autocorrelation calculation unit 5. Figure
3a shows an example of a 20 ms segment of a voiced speech
signal and figure 3b the corresponding autocorrelation
function of the residual signal. It will seen from figure
3a that the actual pitch period is about 5.25 ms corresponding
to 42 samples, and thus the pitch estimation
should end up with this value.
The next step in the estimation of the pitch is to apply
a peak picking algorithm to the autocorrelation function
provided by the unit 5. This is done in the peak detector
6 which identifies the maximum peak (i.e. the largest
value) in the autocorrelation function. The index value,
i.e. the sample number or the lag, of the maximum peak is
then used as a preliminary estimate of the pitch period.
In the case shown in figure 3b it will be seen that the
maximum peak is actually located at a lag of 42 samples.
The search of the maximum peak is only performed in the
range where a pitch period is likely to be located. In
this case the range is set to 60-333 Hz.
However, this basic pitch estimation algorithm is not always
sufficient. In some cases pitch doubling may occur,
i.e. due to distortion the peak in the autocorrelation
function corresponding to the true pitch period is not
the highest peak, but instead the highest peak appears at
twice the pitch period. The highest peak could also appear
at other multiples of the actual pitch period (pitch
tripling, etc.) although this occurs relatively rarely. A
typical example where pitch doubling would arise is shown
in figure 4 which again shows the autocorrelation function
of the residual signal. Here, too, the correct pitch
period would be around 42 samples, but the peak at twice
the pitch period, i.e. around 84 samples, is actually
higher than the one at 42 samples. The basic pitch estimation
algorithm would therefore estimate the pitch period
to 84 samples and pitch doubling would thus occur.
To avoid the problem of pitch doubling the pitch detection
algorithm is therefore improved as described below.
After the preliminary pitch estimate has been determined,
it is checked in the risk check unit 7 whether there is
any risk of pitch doubling. All peaks with a peak value
higher than 75% of the maximum peak are detected and the
further processing depends on the result of this detection.
If only one peak is detected, i.e. the original
maximum peak, there is no need to perform a process to
avoid pitch doubling. In this situation the preliminary
pitch estimate is used as the final pitch estimate. If,
however, more than one peak is detected, there is a risk
of pitch doubling and a further algorithm must be performed
to ensure that the correct peak is selected as the
pitch estimate. This is performed in the unit 8.
To identify the peak corresponding to the actual pitch
period a modified signal is provided based on the location
of the peaks in the autocorrelation of the residual
signal. This modified signal, referred to as binary signal,
consists of only ones and zeros. The binary signal
is set to one where the high peaks are found in the autocorrelation
sequence. All other values are set to zero,
and then the autocorrelation of the binary signal is calculated.
Since there are only values in some positions in
the binary signal, the resulting autocorrelation will
only have a few values separated from zero, and these
values will occur around the pitch period of the signal.
The pitch period is estimated by observing the distance
between the indexes of the values around zero and those
separated from zero. If the group of values separated
from zero contains only a single value, it is selected as
the estimate of the pitch period. If there is more than
one value in the group, the one with the highest amplitude
in the autocorrelation of the residual signal is
chosen.
Sometimes cases may arise where the peak at lag zero is
the only peak present. This situation will occur when a
peak has been split on two samples and there are no other
high peaks in the autocorrelation of the residual signal.
In this case the preliminary pitch estimate is chosen as
the final pitch estimate.
This algorithm is very simple, and therefore it is well
suited in e.g. mobile telephones in which the computational
resources are severely limited, and a demand for a
low-complexity algorithm is thus placed upon the system.
The algorithm may also be implemented in an integrated
circuit which may then be used in other types of equipment.
Although a preferred embodiment of the present invention
has been described and shown, the invention is not restricted
to it, but may also be embodied in other ways
within the scope of the subject-matter defined in the
following claims.
Thus, the autocorrelation function may be calculated directly
of the speech signal instead of the residual signal,
or other conformity functions may be used instead of
the autocorrelation function. As an example, a cross correlation
could be calculated between the speech signal
and the residual signal.
Further, different sampling rates and sizes of the segments
may be used.
Claims (11)
- A method of estimating the pitch of a speech signal (2), said method comprising the steps of:characterized in that the method further comprises the steps of:sampling the speech signal to obtain a series of samples,dividing the series of samples into segments, each segment having a fixed number of consecutive samples,calculating for each segment a conformity function for the signal, anddetecting peaks in the conformity function,providing an intermediate signal derived from the speech signal,converting said intermediate signal to a binary signal, said binary signal being set to logical "1" where the intermediate signal exceeds a pre-selected threshold and to logical "0" where the intermediate signal does not exceed the pre-selected threshold,calculating the autocorrelation of the binary signal, andusing the distance between peaks in the autocorrelation of the binary signal as an estimate of the pitch.
- A method according to claim 1, characterized in that the intermediate signal is provided by filtering the speech signal through a filter (4) based on a set of filter parameters estimated by means of linear predictive analysis (LPA).
- A method according to claim 1, characterized in that the intermediate signal is provided by calculating the autocorrelation of a signal derived from the speech signal by filtering the speech signal through a filter (4) based on a set of filter parameters estimated by means of linear predictive analysis (LPA).
- A method according to any one of claims 1 to 3,
characterized in that it further comprises the step of:selecting, if the peak corresponding to the distance between the peaks is represented by a number of samples, the sample having the maximum amplitude of said conformity function as the estimate of the pitch. - Use of the method according to any one of claims 1 to 4 in a mobile telephone.
- A device adapted to estimate the pitch of a speech signal, and comprising:characterized in that the device further comprises:means (3) for sampling the speech signal to obtain a series of samples,means for dividing the series of samples into segments, each segment having a fixed number of consecutive samples,means (5) for calculating for each segment a conformity function for the signal, andmeans (6) for detecting peaks in the conformity function,means for providing an intermediate signal derived from the speech signal,means (8) for converting said intermediate signal to a binary signal, said binary signal being set to logical "1" where the intermediate signal exceeds a pre-selected threshold and to logical "0" where the intermediate signal does not exceed the pre-selected threshold,means (5) for calculating the autocorrelation of the binary signal, andmeans for using the distance between peaks in the autocorrelation of the binary signal as an estimate of the pitch.
- A device according to claim 6, characterized in that the device is adapted to provide the intermediate signal by filtering the speech signal through a filter (4) based on a set of filter parameters estimated by means of linear predictive analysis (LPA).
- A device according to claim 6, characterized in that the device is adapted to provide the intermediate signal by calculating the autocorrelation of a signal derived from the speech signal by filtering the speech signal through a filter (4) based on a set of filter parameters estimated by means of linear predictive analysis (LPA).
- A device according to any one of claims 6 to 8, characterized in that it is further adapted to select, if the peak corresponding to the distance between the peaks is represented by a number of samples, the sample having the maximum amplitude of said conformity function as the estimate of the pitch.
- A device according to any one of claims 6 to 9, characterized in that the device is a mobile telephone.
- A device according to any one of claims 6 to 9, characterized in that the device is an integrated circuit.
Priority Applications (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP00610034A EP1143412A1 (en) | 2000-04-06 | 2000-04-06 | Estimating the pitch of a speech signal using an intermediate binary signal |
| PCT/EP2001/003493 WO2001077635A1 (en) | 2000-04-06 | 2001-03-27 | Estimating the pitch of a speech signal using a binary signal |
| CN018076890A CN1216361C (en) | 2000-04-06 | 2001-03-27 | Estimating the pitch of a speech signal using a binary signal |
| AU2001273904A AU2001273904A1 (en) | 2000-04-06 | 2001-03-27 | Estimating the pitch of a speech signal using a binary signal |
| US09/826,729 US6954726B2 (en) | 2000-04-06 | 2001-04-05 | Method and device for estimating the pitch of a speech signal using a binary signal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP00610034A EP1143412A1 (en) | 2000-04-06 | 2000-04-06 | Estimating the pitch of a speech signal using an intermediate binary signal |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP1143412A1 true EP1143412A1 (en) | 2001-10-10 |
Family
ID=8174382
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP00610034A Withdrawn EP1143412A1 (en) | 2000-04-06 | 2000-04-06 | Estimating the pitch of a speech signal using an intermediate binary signal |
Country Status (1)
| Country | Link |
|---|---|
| EP (1) | EP1143412A1 (en) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5970441A (en) * | 1997-08-25 | 1999-10-19 | Telefonaktiebolaget Lm Ericsson | Detection of periodicity information from an audio signal |
-
2000
- 2000-04-06 EP EP00610034A patent/EP1143412A1/en not_active Withdrawn
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5970441A (en) * | 1997-08-25 | 1999-10-19 | Telefonaktiebolaget Lm Ericsson | Detection of periodicity information from an audio signal |
Non-Patent Citations (1)
| Title |
|---|
| ALKULAIBI A ET AL: "Fast 3-level binary higher order statistics for simultaneous voiced/unvoiced and pitch detection of a speech signal", SIGNAL PROCESSING. EUROPEAN JOURNAL DEVOTED TO THE METHODS AND APPLICATIONS OF SIGNAL PROCESSING,NL,ELSEVIER SCIENCE PUBLISHERS B.V. AMSTERDAM, vol. 63, no. 2, 1 December 1997 (1997-12-01), pages 133 - 140, XP004102257, ISSN: 0165-1684 * |
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