Voice changer

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The term voice changer (also known as voice enhancer) refers to a device which can change the tone or pitch of or add distortion to the user's voice, or a combination and vary greatly in price and sophistication. A kazoo or a didgeridoo can be used as a makeshift voice changer, though it can be difficult to understand what the person is trying to say.[ citation needed ]

Contents

Hardware implementations

The earliest voice changers were electronic devices usually used over the telephone for the purpose of disguise. There are low-priced, small lithium battery-powered voice changers that are used between a phone's mouthpiece and the user's mouth. [1] [2] [3] [4] [5]

More sophisticated voice changers have different levels of various distortion effects variable by faders. [6] [7]

Software implementations

Nowadays, software implementations are very common. There is a plethora of techniques that modify the voice by using different algorithms. [8] [9] Most algorithms modify the voice by changing the amplitude, pitch and tone of the voice. The pitch plays an important role from changing a male voice into female voice, and vice versa. The results of voice changing through software are quite impressive and satisfactory. [10]

"Voice cloning" software can mimic the sound of a specific person's voice based on recordings of that voice. [11]

Appearances in media

Related Research Articles

Audio signal processing is a subfield of signal processing that is concerned with the electronic manipulation of audio signals. Audio signals are electronic representations of sound waves—longitudinal waves which travel through air, consisting of compressions and rarefactions. The energy contained in audio signals or sound power level is typically measured in decibels. As audio signals may be represented in either digital or analog format, processing may occur in either domain. Analog processors operate directly on the electrical signal, while digital processors operate mathematically on its digital representation.

Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech-to-text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis.

Linear predictive coding (LPC) is a method used mostly in audio signal processing and speech processing for representing the spectral envelope of a digital signal of speech in compressed form, using the information of a linear predictive model.

Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors. Developed in the early 1980s by Robert M. Gray, it was originally used for data compression. It works by dividing a large set of points (vectors) into groups having approximately the same number of points closest to them. Each group is represented by its centroid point, as in k-means and some other clustering algorithms. In simpler terms, vector quantization chooses a set of points to represent a larger set of points.

<span class="mw-page-title-main">PSOLA</span>

PSOLA is a digital signal processing technique used for speech processing and more specifically speech synthesis. It can be used to modify the pitch and duration of a speech signal. It was invented around 1986.

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The Fastest Fourier Transform in the West (FFTW) is a software library for computing discrete Fourier transforms (DFTs) developed by Matteo Frigo and Steven G. Johnson at the Massachusetts Institute of Technology.

<span class="mw-page-title-main">Blind deconvolution</span>

In electrical engineering and applied mathematics, blind deconvolution is deconvolution without explicit knowledge of the impulse response function used in the convolution. This is usually achieved by making appropriate assumptions of the input to estimate the impulse response by analyzing the output. Blind deconvolution is not solvable without making assumptions on input and impulse response. Most of the algorithms to solve this problem are based on assumption that both input and impulse response live in respective known subspaces. However, blind deconvolution remains a very challenging non-convex optimization problem even with this assumption.

Warped linear predictive coding is a variant of linear predictive coding in which the spectral representation of the system is modified, for example by replacing the unit delays used in an LPC implementation with first-order all-pass filters. This can have advantages in reducing the bitrate required for a given level of perceived audio quality/intelligibility, especially in wideband audio coding.

Audio Analytic is a British company headquartered in Cambridge, England that has developed a patented sound recognition software framework called ai3, which provides technology with the ability to understand context through sound. This framework includes an embeddable software platform that can react to a range of sounds such as smoke alarms and carbon monoxide alarms, window breakage, infant crying and dogs barking.

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Cepstral mean and variance normalization (CMVN) is a computationally efficient normalization technique for robust speech recognition. The performance of CMVN is known to degrade for short utterances. This is due to insufficient data for parameter estimation and loss of discriminable information as all utterances are forced to have zero mean and unit variance.

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Music can be described and represented in many different ways including sheet music, symbolic representations, and audio recordings. For each of these representations, there may exist different versions that correspond to the same musical work. The general goal of music alignment is to automatically link the various data streams, thus interrelating the multiple information sets related to a given musical work. More precisely, music alignment is taken to mean a procedure which, for a given position in one representation of a piece of music, determines the corresponding position within another representation. In the figure on the right, such an alignment is visualized by the red bidirectional arrows. Such synchronization results form the basis for novel interfaces that allow users to access, search, and browse musical content in a convenient way.

<span class="mw-page-title-main">Chroma feature</span>

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Enhanced Voice Services (EVS) is a superwideband speech audio coding standard that was developed for VoLTE and VoNR. It offers up to 20 kHz audio bandwidth and has high robustness to delay jitter and packet losses due to its channel aware coding and improved packet loss concealment. It has been developed in 3GPP and is described in 3GPP TS 26.441. The application areas of EVS consist of improved telephony and teleconferencing, audiovisual conferencing services, and streaming audio. Source code of both decoder and encoder in ANSI C is available as 3GPP TS 26.442 and is being updated regularly. Samsung uses the term HD+ when doing a call using EVS.

WaveNet is a deep neural network for generating raw audio. It was created by researchers at London-based AI firm DeepMind. The technique, outlined in a paper in September 2016, is able to generate relatively realistic-sounding human-like voices by directly modelling waveforms using a neural network method trained with recordings of real speech. Tests with US English and Mandarin reportedly showed that the system outperforms Google's best existing text-to-speech (TTS) systems, although as of 2016 its text-to-speech synthesis still was less convincing than actual human speech. WaveNet's ability to generate raw waveforms means that it can model any kind of audio, including music.

<span class="mw-page-title-main">Generative audio</span> Creation of audio files from databases of audio clips

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A copy detection pattern (CDP) or graphical code is a small random or pseudo-random digital image which is printed on documents, labels or products for counterfeit detection. Authentication is made by scanning the printed CDP using an image scanner or mobile phone camera. It is possible to store additional product-specific data into the CDP that will be decoded during the scanning process. A CDP can also be inserted into a 2D barcode to facilitate smartphone authentication and to connect with traceability data.

References

  1. https://www.youtube.com/watch?v=eRdSi4gJz98&t=60s
  2. https://blog.adafruit.com/2012/10/11/how-to-wave-shield-voice-changer-adafruit-learning-system/
  3. https://web.archive.org/web/20210413003715/https://kidzlane.com/products/voice-changer-megaphone
  4. http://www.unitone.com.tw/PAD/Televoicer.htm
  5. https://www.fun-world.net/halloween/costume-accessories/misc/9291.html
  6. https://www.maono.com/products/amc2-neo-and-pd200x-all-in-one-streaming-audio-production-studio
  7. https://helpguide.sony.net/has/mhc-v42d/v1/es/contents/TP0002339590.html
  8. Abe, M.; Nakamura, S.; Shikano, K.; Kuwabara, H. (April 1988). "Voice conversion through vector quantization". ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing. pp. 655–658 vol.1. doi:10.1109/ICASSP.1988.196671. S2CID   62203146.
  9. Hui Ye; Young, S. (May 2004). "High quality voice morphing". 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing. Vol. 1. pp. I–9. doi:10.1109/ICASSP.2004.1325909. ISBN   0-7803-8484-9. S2CID   14019057.
  10. Ahmed, I.; Sadiq, A.; Atif, M.; Naseer, M.; Adnan, M. (February 2018). "Voice morphing: An illusion or reality". 2018 International Conference on Advancements in Computational Sciences (ICACS). pp. 1–6. doi:10.1109/ICACS.2018.8333282. ISBN   978-1-5386-2172-1. S2CID   4775311.
  11. Brayne, Sarah (2018). "Visual Data and the Law". Law & Social Inquiry. 43 (4): 1149–1163. doi:10.1111/lsi.12373. PMC   10857868 . S2CID   150076575.