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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. 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.
The mel scale is a perceptual scale of pitches judged by listeners to be equal in distance from one another. The reference point between this scale and normal frequency measurement is defined by assigning a perceptual pitch of 1000 mels to a 1000 Hz tone, 40 dB above the listener's threshold. Above about 500 Hz, increasingly large intervals are judged by listeners to produce equal pitch increments.
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.
Keyword spotting is a problem that was historically first defined in the context of speech processing. In speech processing, keyword spotting deals with the identification of keywords in utterances.
The problem of reconstruction from zero crossings can be stated as: given the zero crossings of a continuous signal, is it possible to reconstruct the signal? Worded differently, what are the conditions under which a signal can be reconstructed from its zero crossings?
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.
Scale-space segmentation or multi-scale segmentation is a general framework for signal and image segmentation, based on the computation of image descriptors at multiple scales of smoothing.
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.
The IEEE Signal Processing Society is one of the nearly 40 technical societies of the Institute of Electrical and Electronics Engineers (IEEE) and the first one created. Its mission is to "advance and disseminate state-of-the-art scientific information and resources; educate the signal processing community; and provide a venue for people to interact and exchange ideas."
In applied mathematics, a bit-reversal permutation is a permutation of a sequence of items, where is a power of two. It is defined by indexing the elements of the sequence by the numbers from to , representing each of these numbers by its binary representation, and mapping each item to the item whose representation has the same bits in the reversed order.
Financial signal processing is a branch of signal processing technologies which applies to signals within financial markets. They are often used by quantitative analysts to make best estimation of the movement of financial markets, such as stock prices, options prices, or other types of derivatives.
In communications technology, the technique of compressed sensing (CS) may be applied to the processing of speech signals under certain conditions. In particular, CS can be used to reconstruct a sparse vector from a smaller number of measurements, provided the signal can be represented in sparse domain. "Sparse domain" refers to a domain in which only a few measurements have non-zero values.
An audio coding format is a content representation format for storage or transmission of digital audio. Examples of audio coding formats include MP3, AAC, Vorbis, FLAC, and Opus. A specific software or hardware implementation capable of audio compression and decompression to/from a specific audio coding format is called an audio codec; an example of an audio codec is LAME, which is one of several different codecs which implements encoding and decoding audio in the MP3 audio coding format in software.
In Western music, the term chroma feature or chromagram closely relates to twelve different pitch classes. Chroma-based features, which are also referred to as "pitch class profiles", are a powerful tool for analyzing music whose pitches can be meaningfully categorized and whose tuning approximates to the equal-tempered scale. One main property of chroma features is that they capture harmonic and melodic characteristics of music, while being robust to changes in timbre and instrumentation.
The IARPA Babel program developed speech recognition technology for noisy telephone conversations. The main goal of the program was to improve the performance of keyword search on languages with very little transcribed data, i.e. low-resource languages. Data from 26 languages was collected with certain languages being held-out as "surprise" languages to test the ability of the teams to rapidly build a system for a new language.
Steven Glenn Johnson is an American mathematician known for being a co-creator of the FFTW library for software-based fast Fourier transforms and for his work on photonic crystals. He is professor of Applied Mathematics and Physics at MIT where he leads a group on Nanostructures and Computation.
Matti Antero Karjalainen was a Finnish speech processing researcher and inventor in the fields of speech synthesis, speech analysis, speech technology, audio signal processing and psychoacoustics. He was the head of Acoustics Laboratory at the Helsinki University of Technology from 1980 to 2006.
Namrata Vaswani is an Indian-American electrical engineer known for her research in compressed sensing, robust principal component analysis, signal processing, statistical learning theory, and computer vision. She is a Joseph and Elizabeth Anderlik Professor in Electrical and Computer Engineering at Iowa State University, and a professor of mathematics at Iowa State.
References
- ↑ Rabiner (1984). "The Acoustics, Speech, and Signal Processing Society. A Historical Perspective" (PDF). Retrieved 23 January 2018.
{{cite journal}}: Cite journal requires|journal=(help) - ↑ SoC Conference Ranking Archived 2011-03-10 at the Wayback Machine
- ↑ Conference Ranks
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