Voice transformation refers to the many changes one can apply on a voice, specifically speaking or singing, without changing the actual voice itself. Since speech recognition software already has the ability to identify the characteristics of a voice, transforming it into an artificially intelligent (ASI) voice, may prove to be a better option. Voice transformation is generally found to be an extra or detached part in speech recognition systems because it can produce virtual voices in an easy and versatile manner. With speech recognition technology is becoming more popular among users, voice transformation is slowly making its way into everyday life.
Examples of Voice Transformations
One example of voice transformation that was introduced by A. K. Roy, who is a professor at Columbia University’s School of Engineering, is known as ‘A.K. Roy Synthesized Speech’. This speech recognition application is incorporated in the Microsoft Windows operating system. It allows the user to speak in monophonic (all tones) or polyphonic (two tone) voice. It can also apply basic voice transformation techniques such as ‘voice box reconstruction’ and ‘voice breaking.’ Other features include recognition of tone, pitch, rhythm, timing and inflection.
This speech recognition application is just one of the many applications in this domain. The ability to transform voice signals is quite new to speech recognition technology. Patent authorities are granting growing numbers of patents for the same reason. Transforming speech signals is actually a much broader area than the mere application of speech recognition software. Patent authorities are not just confining themselves to mere speech recognition, they are pursuing technology with the aim of making the entire process of patenting and licensing substantially easier.
The advancement of technology makes it possible to voice transformation techniques to be applied in non-traditional patenting areas such as biotechnology, nanotechnology, genetics, computer science etc. Non-traditional voice patenting encompasses new technologies for electronic and electrical devices, nanotechnology, biotechnology etc. It also encompasses speech synthesis systems. Thus, we can say that voice transformation technologies can cover a broad range of new technologies which had not even remotely thought about while drafting the patent specification. The fact that it is a relatively new field has only worsened its commercial prospects. However, the future is undoubtedly bright as voice transformation technologies are likely to receive significant patenting improvements.
It is essential to note that the voice quality transformation algorithm is not capable of modifying the source and target speakers digitally. However, it can be used to change the quality of the source speech and target speech digitally. That is, speech transformation algorithms can be used to apply quality adjustments in speech source and target speeches so as to achieve a higher degree of speech quality and consistency regardless of the source and target speakers. These improvements might be achieved by adjusting the characteristics of the source speech or the characteristics of the target speech or both.
The advancements that have been made in speech recognition technology are enormous. Advances in speech recognition software have made it possible for speech recognition to handle a wide range of tasks, including speech synthesis. Synthesized speech could then be sent to text file formats such as PDF or rendered into speech using voice-recognition software. This makes it easier for speech recognition software to handle the large volume of data which is currently being used in the business environment.
Voice transformation is often used to transform a monotonous speech, or speech that is boring or contains repetitive phrases or sentence structure, into a speech which is more interesting and informative, and thus more enjoyable to listen to or better able to retain. It can also be used to transform a monotonous or boring speech, or one that contains repetitious phrases, into a speech that contains information that is specific to the company and its employees. A good voice transformer is able to accomplish this easily and naturally, by applying the mathematical rules of compression. For example, when a voice message is compressed from a series of audio messages, the original source speaker’s voice is left out.
Some voice transformers are capable of speech synthesis, where they take the original audio message, and surgically remove parts of it that do not contribute to the message being delivered. The parts that remain are then combined with the target speaker’s voice in order to create the desired transformed speech. Some voice transformers are capable of speech synthesis and also glottal source detection; they take the original voice recording and surgically remove the high-frequency content (glottal) which occurs when a person speaks with their mouth closed. When a person speaks, their hands are unable to fully capture all of the high-frequency vibrations, which is why voice transformation makes it easier to speech synthesize.