Abstract:
A method and system provide for run-time modification of synthesized speech. The method includes the step of generating synthesized speech based on textual input and a plurality of run-time control parameter values. Real-time data is generated based on an input signal, where the input signal characterizes an intelligibility of the speech with regard to a listener. The method further provides for modifying one or more of the run-time control parameter values based on the real-time data such that the intelligibility of the speech increases. Modifying the parameter values at run-time as opposed to during the design stages provides a level of adaptation unachievable through conventional approaches.

Description:
BACKGROUND OF THE INVENTION 
   1. Field of the Invention 
   The present invention generally relates to speech synthesis. More particularly, the present invention relates to a method and system for improving the intelligibility of synthesized speech at run-time based on real-time data. 
   2. Discussion 
   In many environments such as automotive cabins, aircraft cabins and cockpits, and home and office, systems have been developed to improve the intelligibility of audible sound presented to a listener. For example, recent efforts to improve the output of automotive audio systems have resulted in equalizers that can either manually or automatically adjust the spectral output of the audio system. While this has traditionally been done in response to the manipulation of various controls by the listener, more recent efforts have involved audio sampling of the listener&#39;s environment. The audio system equalization approach typically requires a significant amount of knowledge regarding the expected environment in which the system will be employed. Thus, this type of adaptation is limited to the audio system output and is, in the case of a car, typically fixed to a particular make and model of the car. 
   In fact, the phonetic spelling alphabet (i.e., alpha, bravo, Charlie, . . . ) has been used for many years in air-traffic and military-style communications to disambiguate spelled letters under severe conditions. This approach is therefore also based on the underlying theory that certain sounds are inherently more intelligible than others in the presence of channel and/or background noise. 
   Another example of intelligibility improvement involves signal processing within cellular phones in order to reduce audible distortion caused by transmission errors in uplink/downlink channels or in the basestation network. It is important to note that this approach is concerned with channel (or convolutional) noise and fails to take into account the background (or additive) noise present in the listener&#39;s environment. Yet another example is the conventional echo cancellation system commonly used in teleconferencing. 
   It is also important to note that all of the above techniques fail to provide a mechanism for modifying synthesized speech at run-time. This is critical since speech synthesis is rapidly growing in popularity due to recent strides made in improving the output of speech synthesizers. Notwithstanding these recent achievements, a number of difficulties remain with regard to speech synthesis. In fact, one particular difficulty is that all conventional speech synthesizers require prior knowledge of the anticipated environment in order to set the various control parameter values at the time of design. It is easy to understand that such an approach is extremely inflexible and limits a given speech synthesizer to a relatively narrow set of environments in which the synthesizer can be used optimally. It is therefore desirable to provide a method and system for modifying synthesized speech based on real-time data such that the intelligibility of the speech increases. 
   The above and other objectives are provided by a method for modifying synthesized speech in accordance with the present invention. The method includes the step of generating synthesized speech based on textual input and a plurality of run-time control parameter values. Real-time data is generated based on an input signal, where the input signal characterizes an intelligibility of the speech with regard to a listener. The method further provides for modifying one or more of the run-time control parameter values based on the real-time data such that the intelligibility of the speech increases. Modifying the parameter values at run-time as opposed to during the design stages provides a level of adaptation unachievable through conventional approaches. 
   Further in accordance with the present invention, a method for modifying one or more speech synthesizer run-time control parameters is provided. The method includes the steps of receiving real-time data, and identifying relevant characteristics of synthesized speech based on the real-time data. The relevant characteristics have corresponding run-time control parameters. The method further provides for applying adjustment values to parameter values of the control parameters such that the relevant characteristics of the speech change in a desired fashion. 
   In another aspect of the invention, a speech synthesizer adaptation system includes a text-to-speech (TTS) synthesizer, an audio input system, and an adaptation controller. The synthesizer generates speech based on textual input and a plurality of run-time control parameter values. The audio input system generates real-time data based on various types of background noise contained in an environment in which the speech is reproduced. The adaptation controller is operatively coupled to the synthesizer and the audio input system. The adaptation controller modifies one or more of the run-time control parameter values based on the real-time data such that interference between the background noise and the speech is reduced. 
   It is to be understood that both the foregoing general description and the following detailed description are merely exemplary of the invention, and are intended to provide an overview or framework for understanding the nature and character of the invention as it is claimed. The accompanying drawings are included to provide a further understanding of the invention, and are incorporated in and constitute part of this specification. The drawings illustrate various features and embodiments of the invention, and together with the description serve to explain the principles and operation of the invention. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The various advantages of the present invention will become apparent to one skilled in the art by reading the following specification and sub-joined claims and by referencing the following drawings, in which: 
       FIG. 1  is a block diagram of a speech synthesizer adaptation system in accordance with the principles of the present invention; 
       FIG. 2  is a flowchart of a method for modifying synthesized speech in accordance with the principles of the present invention; 
       FIG. 3  is a flowchart of a process for generating real-time data based on an input signal according to one embodiment of the present invention; 
       FIG. 4  is a flowchart of a process for characterizing background noise with real-time data in accordance with one embodiment of the present invention; 
       FIG. 5  is a flowchart of a process for modifying one or more run-time control parameter values in accordance with one embodiment of the present invention; and 
       FIG. 6  is a diagram illustrating relevant characteristics and corresponding run-time control parameters according to one embodiment of the present invention. 
   

   DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
   Turning now to  FIG. 1 , a preferred speech synthesizer adaptation system  10  is shown. Generally, the adaptation system  10  has a text-to-speech (TTS) synthesizer  12  for generating synthesized speech  14  based on textual input  16  and a plurality of run-time control parameter values  42 . An audio input system  18  generates real-time data (RTD)  20  based on background noise  22  contained in an environment  24  in which the speech  14  is reproduced. An adaptation controller  26  is operatively coupled to the synthesizer  12  and the audio input system  18 . The adaptation controller  26  modifies one or more of the run-time control parameter values  42  based on the real-time data  20  such that interference between the background noise  22  and the speech  14  is reduced. It is preferred that the audio input system  18  includes an acoustic-to-electric signal converter such as a microphone for converting sound waves into an electric signal. 
   The background noise  22  can include components from a number of sources as illustrated. The interference sources are classified depending on the type and characteristics of the source. For example, some sources such as a police car siren  28  and passing aircraft (not shown) produce momentary high level interference often of rapidly changing characteristics. Other sources such as operating machinery  30  and air-conditioning units (not shown) typically produce continuous low level stationery background noise. Yet, other sources such as a radio  32  and various entertainment units (not shown) often produce ongoing interference such as music and singing with characteristics similar to the synthesized speech  14 . Furthermore, competing speakers  34  present in the environment  24  can be a source of interference having attributes practically identical to those of the synthesized speech  14 . In addition, the environment  24  itself can affect the output of the synthesized speech  14 . The environment  24 , and therefore also its effect, can change dynamically in time. 
   It is important to note that although the illustrated adaptation system  10  generates the real-time data  20  based on background noise  22  contained in the environment  24  in which the speech  14  is reproduced, the invention is not so limited. For example, as will be described in greater detail below, the real-time data  20  may also be generated based on input from a listener  36  via input device  19 . 
   Turning now to  FIG. 2 , a method  38  is shown for modifying synthesized speech. It can be seen that at step  40 , synthesized speech is generated based on textual input  16  and a plurality of run-time control parameter values  42 . Real-time data  20  is generated at step  44  based on an input signal  46 , where the input signal  46  characterizes an intelligibility of the speech with regard to a listener. As already mentioned, the input signal  46  can originate directly from the background noise in the environment, or from a listener (or other user). Nevertheless, the input signal  46  contains data regarding the intelligibility of the speech and therefore represents a valuable source of information for adapting the speech at run-time. At step  48 , one or more of the run-time control parameter values  42  are modified based on the real-time data  20  such that the intelligibility of the speech increases. 
   As already discussed, one embodiment involves generating the real-time data  20  based on background noise contained in an environment in which the speech is reproduced. Thus,  FIG. 3  illustrates a preferred approach to generating the real-time data  20  at step  44 . Specifically, it can be seen that the background noise  22  is converted into an electrical signal  50  at step  52 . At step  54 , one or more interference models  56  are retrieved from a model database (not shown). Thus, the background noise  22  can be characterized with the real-time data  20  at step  58  based on the electrical signal  50  and the interference models  56 . 
     FIG. 4  demonstrates the preferred approach to characterizing the background noise at step  58 . Specifically, it can be seen that at step  60 , a time domain analysis is performed on the electrical signal  50 . The resulting time data  62  provides a great deal of information to be used in operations described herein. Similarly, at step  64 , a frequency domain analysis is performed on the electrical signal  50  to obtain frequency data  66 . It is important to note that the order in which steps  60  and  64  are executed is not critical to the overall result. 
   It is also important to note that the characterizing step  58  involves identifying various types of interference in the background noise. These examples include, but are not limited to, high level interference, low level interference, momentary interference, continuous interference, varying interference, and stationary interference. The characterizing step  58  may also involve identifying potential sources of the background noise, identifying speech in the background noise, and determining the locations of all these sources. 
   Turning now to  FIG. 5 , the preferred approach to modifying the run-time control parameter values  42  is shown in greater detail. Specifically, it can be seen that at step  68  the real-time data  20  is received, and at step  70  relevant characteristics  72  of the speech are identified based on the real-time data  20 . The relevant characteristics  72  have corresponding run-time control parameters. At step  74  adjustment values are applied to parameter values of the control parameters such that the relevant characteristics  72  of the speech change in a desired fashion. 
   Turning now to  FIG. 6 , potential relevant characteristics  72  are shown in greater detail. Generally, the relevant characteristics  72  can be classified into speaker characteristics  76 , emotion characteristics  77 , dialect characteristics  78 , and content characteristics  79 . The speaker characteristics  76  can be further classified into voice characteristics  80  and speaking style characteristics  82 . Parameters affecting voice characteristics  80  include, but are not limited to, speech rate, pitch (fundamental frequency), volume, parametric equalization, formants (formant frequencies and bandwidths), glottal source, tilt of the speech power spectrum, gender, age and identity. Parameters affecting speaking style characteristics  82  include, but are not limited to, dynamic prosody (such as rhythm, stress and intonation), and articulation. Thus, over-articulation can be achieved by fully articulating stop consonants, etc., potentially resulting in better intelligibility. 
   Parameters relating to emotion characteristics  77 , such as urgency, can also be used to grasp the listener&#39;s attention. Dialect characteristics  78  can be affected by pronunciation and articulation (formants, etc.). It will further be appreciated that parameters such as redundancy, repetition and vocabulary relate to content characteristics  79 . For example, adding or removing redundancy in the speech by using synonym words and phrases (such as 5 PM=five pm versus five o&#39;clock in the afternoon). Repetition involves selectively repeating portions of the synthesized speech in order to better emphasize important content. Furthermore, allowing a limited vocabulary and limited sentence structure to reduce perplexity of the language might also increase intelligibility. 
   Returning now to  FIG. 1 , it will be appreciated that polyphonic audio processing can be used in conjunction with an audio output system  84  to spatially reposition the speech  14  based on the real-time data  20 . 
   Those skilled in the art can now appreciate from the foregoing description that the broad teachings of the present invention can be implemented in a variety of forms. Therefore, while this invention can be described in connection with particular examples thereof, the true scope of the invention should not be so limited since other modifications will become apparent to the skilled practitioner upon a study of the drawings, specification and following claims.