Abstract:
Utterances by a speaker are analyzed by an appropriate computational system. The spoken words are recognized and indexed to their respective analogs which are used to tailor the speech sequence to conform to a pre-determined standard of speech characteristics which could be fixed for a given language or chosen based on the regional characteristics of the said common language target for a communication session. Thusly selected audio sequences are then tailored or synthesized into the normalized characteristics and inserted into the outgoing speech stream such that the resulting audio sequence exhibits reduced speech characteristics deemed undesirable.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
       [0001]    This Application claims the benefit of Provisional Application Ser. No. 60/889,938 filed 15 Feb. , 2007. 
     
    
     FIELD OF INVENTION 
       [0002]    This invention relates generally to enhancements to uttered speech, and particularly to the means of normalizing speech in which a speaker&#39;s pronunciation, intonation and/or other speech characteristics are undesirable. Specifically, this invention relates to digital processing techniques applied to auditory sequences which effectively normalize the apparent accent in the speech. This invention in addition relates to digital noise- cancelling techniques utilizing digital processing to increase effective signal-to-noise ratio of verbal communications. 
       BACKGROUND 
       [0003]    One of the serious problems arising in verbal communications is the presence of diverse accents of individuals speaking a common language. While phonetically the utterances of certain words by an individual may be consistent, their enunciation can make his speech difficult or impossible to understand by others unfamiliar with the speaker&#39;s accent. With proliferation of international business, global business functions outsourcing and growth of multinational companies whose offices span divers countries, serious challenges to effective communications arise from dissimilar accents of speakers who may not share a common pronunciation or a common mother-tongue. Another problem arises in voice communications in situations where high ambient noise is present at least on one end of the voice communication link. Such high ambient noise environments may include, but not limited to, a battlefield, a moving vehicle, an industrial plant, and various large assemblages of people, such as parades, celebrations, concerts, etc. In the presence of noise in the incoming speech, a listener will normally strain and try to maximize his attention in the attempt to understand the other party. What he is effectively doing is increasing the processing gain of his cognitive speech recognition mechanism. If the speaker&#39;s speech is familiar to the listener, the listener&#39;s understanding level will be higher than in the case of unfamiliar speech. 
         [0004]    Present invention converts any speaker&#39;s speech to a standard pronunciation while simultaneously virtually eliminating background noise. 
       PRIOR ART 
       [0005]    Processing of speech, both analog and digital, performed for varied purposes is well known in the art. Digital speech compression for transmission bandwidth minimization, noise filtering, frequency shifting are some of the examples of such processing and are well-known in the art. 
         [0006]    Speech recognition techniques are also well known in the prior art and tend to focus on complex algorithms to convert speech to text. Likewise, techniques for speech decompression synthesis as well as completely synthetic speech and sentence construction are also well known. 
         [0007]    None of the prior art however discloses a speech filter as disclosed and claimed herein wherein a speaker articulates in one language using some of the rules or sounds of another language or dialect, or where his articulation is determined by where he lives and what social groups he belongs to. 
         [0008]    Likewise, none of the prior art discloses a noise-cancellation technique for voice communications which is based on speech-recognition techniques of the present invention. 
       SUMMARY OF THE INVENTION 
       [0009]    In accordance with the present invention utterances by a speaker are analyzed by an appropriate computational system. The spoken words are recognized and indexed to their respective analogs which are used to tailor the speech sequence to conform to a pre-determined standard of speech characteristics which could be adjusted for a given language, or chosen based on the regional characteristics of the said common language target for a communication session. Thusly selected audio sequences are then tailored or synthesized into the normalized characteristics and inserted into the outgoing speech stream such that the spoken audio sequence exhibits reduced speech characteristics which may be undesirable while substantially preserving generalized speech characteristics specific to a speaker, such as tempo, pitch, and overall sentence inflection . 
         [0010]    The noise-cancellation features of this invention rely on recognition of the speaker&#39;s utterances in the presence of noise and reconstructing them in a way to maximize their comprehension by a listener. Additionally, in the presence of noise at the receiving end of communications, the output speech can be adjusted to maximize its intelligibility. 
       OBJECTS AND ADVANTAGES 
       [0011]    Generalized objects and advantages of the present invention include: Normalization of speech sequences contained in an audio stream which are phonically in bounds of a predetermined set of parameters, and respectively altering an audio stream which falls outside of the bounds of a predetermined set of parameters, the determination being based on sound sequence and contextual usage. 
         [0012]    Reducing computational load on systems resultant from this invention such that these systems can be operated with nominal latency such that users perceive near- or full real-time operation. 
         [0013]    Support for a large variety of speech parameters such that users can select normalized output formats based on a common language and/or dialect, or high ambient noise conditions. 
         [0014]    Use of speech recognition to effectively remove noise from the output speech by effectively increasing the signal-to-noise ratio with digital speech processing. 
         [0015]    Use of speech training to increase accuracy and reduce computational loads of speech altering systems though a unique application of speech recognition technology. 
         [0016]    It should be recognized by those skilled in the art that while the normalization of speaker enunciation in audio sequence is used as an illustrative example the modification of syntax, reformatting of sentence structure and/or the use of multiple common parameter sets of common or divers languages is contemplated. While preferred embodiments are shown, they should not be construed as limiting. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS  
         [0017]    FIG.  1 —Shows a functional block diagram of one embodiment of the invention 
           [0018]    FIG.  2 —Shows a detailed block diagram of one embodiment of the invention 
           [0019]    FIG.  3 —Shows a detailed block diagram of the embodiment of the invention for multi-language implementation. 
           [0020]    FIG.  4 —Shows a detailed block diagram of the operation of the invention on a phoneme level 
           [0021]    FIG.  5 —Shows a system embodiment of the invention 
       
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENT 
       [0022]    This invention requires the input of human speech. Speech can be represented as an analog wave that varies over time and has a smooth, continuous curve. The height of the wave represents intensity (loudness), and the shape of the wave represents frequency (pitch). The continuous curve of the wave accommodates a multiplicity of possible values. It is known in the prior art to convert these values into a set of discrete values, using a process called digitization. 
         [0023]      FIG. 1  shows a simplified concept of the invention. Speech is input via process  2  and subsequently digitized in process  4 . The speech recognition process  6  attempts to parse the utterances into distinct words and recognize them. If recognition is successful a pronunciation database  8  is queried for the proper pronunciation description instance of the recognized word by process  12 . If a proper pronunciation description of the recognized word exists, it is used by process  14  to synthesize the actual ‘proper’ waveform of the word which is substituted into the speech stream by process  16 . If, however, the word is not recognized or its recognized but a pronunciation description cannot be found, the original utterance is retained in the output speech stream by process  10 . 
         [0024]      FIG. 2  shows a refinement of the process in  FIG. 1  where the speech is input via process  18  and subsequently digitized in process  20 . Speech recognition process  22  attempts to parse the utterances into distinct words and recognize them. If recognition is successful pronunciation database  26  is queried for the proper pronunciation description instance of the recognized word by process  28 . If a proper pronunciation description of the recognized word exists, it is used by process  30  to synthesize the actual ‘proper’ waveform of the utterance. This synthesized version of the ‘properly pronounced’ word is then compared with the digitized version of the original utterance by process  24  which determines if the two are ‘close’ per the built-in comparison rules. If the two are ‘close’, the original utterance is used without alteration for output via process  34 . Otherwise, the ‘properly’ pronounced utterance is substituted into the speech stream by process  32   
         [0025]    As shown in  FIG. 5  when “discrete utterance” information is presented to this invention in analog form via speech input device  62 , an analog-digital converter also known as digitizer  64  is used to convert the analog digital signals sampled at a fixed rate into blocks of data such as 260 bits for every set of original samples such as containing 160 units. This invention then provides this digitized voice to a coding algorithm residing in controller  66  and memory  68  selected from a member of the linear predictive analysis-by-synthesis (LPAS) family of coding algorithms. As is the case with all LPAS algorithms, speech is represented using two sets of parameters: information about the Linear predictive coding (LPC) filter (in the form of quantized log area ratios, or Q-LARS) and information about the coded residual signal in the form of quantized Regular Pulse Excited Long Term Prediction (RPE-LTP parameters). The original analog system can be sampled at a differing rate for presentation to a digital speech recognition algorithm. Once the digital speech recognition has completed by controller  66  a conversion of a number of discrete utterances into binary patterns representing one or more words the binary patterns are presented to a synthesizer  68  which converts the binary patterns of words into binary patterns of synthesized speech. This synthesized speech represents an extremely artificial but highly repeatable representation of the original discreet utterances. This interim representation of the deconstructed speech may now be used to alter the reconstruction of the original speech waveforms. 
         [0026]    Typical reconstruction is achieved by convolution of the impulse response of the LPC filter with the residual signal and the spectrum of the speech and the waveform can be estimated by adding the spectra of the LPC filter and of the residual. By establishing an algorithmic relationship between the known word pattern, the original voice coded Q-LARS and RPE-LTP parameters, the normalized Q-LARS and RPE-LTP indexed from synthesis and the original digital voice representation can be derived and output via speech output device  70 . 
         [0027]    Alternately, as shown in  FIG. 4  an analog signal upon input  72  can be repeatedly quantized where each sample results in a set of bits. Before sampling and digitizing process  76 , the converter pre-filters the signal via a band -pass filtering process  74  so that most of it lies between 300 and 3400 Hz which is recognized as the frequency band containing most of the human speech information. In addition to sampling speech, the indexing of pauses is used to sample background noises and remove them from the data. 
         [0028]    Subsequently the invention compares the sampled sound to known characteristics of human speech and removes obvious noise. The system then locates phonemes via process  78  within the string of incoming values and generates digital representations of pre-determined ‘perfect’ phoneme via process  80 . Compression processes  82  and  84  are used on the sampled and digitized speech and ‘perfect phoneme’ representations respectively to decrease the computational load on the system in processing. 
         [0029]    Computational process  78  is used to recognize obvious phonemes as well as classification of phonemes based on linguistic bodies of knowledge into which phonemes typically follow others. These conjectures are aided by training of patterns of the current user speech. 
         [0030]    Once the system of the current invention has completed conversion of a number of discrete utterances into binary patterns representing one or more phonemes as the binary patterns, it combines multiple phonemes into morphemes and words. Once the probable phoneme, morphemes and context is registered, the indexing of the higher level phoneme/morpheme patterns is performed by the system. 
         [0031]    In parallel to the indexing process as described above, the speaker&#39;s voice is sampled at a fixed rate into blocks of data such as 260 bits for every set of original samples such as  160  and then coded using an algorithm selected from a member of the linear predictive analysis-by-synthesis (LPAS) family of coding algorithms. As is the case with all LPAS algorithms, speech is represented using two sets of parameters: information about LPC filter (in the form of quantized log area ratios, or Q-LARS) and information about the coded residual signal in the form of quantized Regular Pulse Excited Long Term Prediction (RPE-LTP parameters) all of which are well represented in the prior art. 
         [0032]    The normalized speech resultant from the current invention is achieved by remapping the original voice Q-LARS and RPE-LTP parameters based on an indexing of the higher level phoneme/morpheme patterns and a priori knowledge of Q-LARS and RPE-LTP parameters derived from the normalized indexing of phoneme/morpheme patterns. Using the speech recognition the invention forms a notional model of what sound patters are needed. The source code model provides a generalized magnitude of corrective insertion by comparing the coded representation of the speech to equivalent normalized pattern derived from the recognition process. 
         [0033]    With the original speech sequence, the temporal locations of speech which is outside of the normalized window and the magnitude of these offsets from the normalized speech target the invention passes portions of the voice without modification when these portions are within the normalized target window in process  94 , after applying threshold  90  which in turn is subject to pre-determined rules  92 . 
         [0034]    If, however, voice inputs extend beyond the normalized threshold  90  of a given language as determined by comparing actual compressed source modeled speech with template source modeled speech as indexed by the voice recognition function, the corrected sequence is substituted instead of the original speech in process  98 . 
         [0035]    The correction to the speech by process  96  is made by interpolating between the waveform compressed voice sequence and a projected waveform compressed voice sequence which using a quantization table derived from the actual voice and by using pre-determined weighing coefficients  88 . This corrected voice sequence can be used directly via process  98 , however the degree of offset from the source model will provide an ideal weighting to allow seamless integration into the voice sequence. 
       ADDITIONAL EMBODIMENTS 
       [0036]      FIG. 3  shows an additional embodiment of the present invention where users are given a choice of several languages or dialects for communications. Upon initiation of communication session via process  36 , subsequent process  38  loads default language ‘A’ selection supported by speech recognition database  44 , pronunciation database  46  and syntax rules database  48 . The communication session then proceeds as described in previous embodiments via a processes  40 ,  58  and  60 . If it&#39;s determined via process  42  that an alternate language or dialect is more appropriate, alternative language ‘B’ selection is made via process  50 , which is supported by its speech recognition database  52 , pronunciation database  54  and syntax rules database  56 . The session is ten proceeds in theis language or dialect via process  60 . 
         [0037]    It is anticipated that one skilled in the art will recognize that the same methods, apparatuses and systems can be used to enhance communications between individuals and/or groups in environments which include, but not limited to ambient noises such as automotive, road, battlefield, industrial and crowd sounds. Present invention converts any speaker&#39;s speech to a standard pronunciation while simultaneously virtually eliminates background noise. 
         [0038]    Additionally, the system of present invention, by using speech recognition and being trainable for a particular speaker&#39;s speech, acts as a ‘familiarizer’ of the speaker&#39;s speech, thus removing this burden from the listener. This further enhances speech intelligibility and understanding in high-stress situations. Those skilled in the art will also recognize the application of this invention in public service applications such as but not limited to emergency services, crime tip lines, and social services. 
         [0039]    Additionally, persons with various speech impediments, such as lisp, stuttering, stammering, lallation, lambdacisms, cataphasia, etc. would be able to converse more or less normally with others, the only requirement being that their speech be processed by the system of the instant invention, recognized by it, and then re-played. Even whole sentence fragments, such as undesirable utterances and ‘filler’ words can be reduced in occurrence or eliminated, at will. 
         [0040]    Although descriptions provided above contain many specific details, they should not be construed as limiting the scope of the present invention. Thus, the scope of this invention should be determined from the appended claims and their legal equivalents.