Civil Rights
Movements, leaders, victories and the continuing fight for equality.
q2K BHP
Black History Portal
THE BHP WIRE —
HIDDEN TRUTHS
What's New!
Explore the people, places, events, achievements, struggles and stories that shaped our journey.
Movements, leaders, victories and the continuing fight for equality.
Innovation, patents, science, technology and world-changing contributions.
Pioneers, champions, Negro Leagues, records, activism and excellence.
Meet the people whose lives, choices and achievements shaped the journey.
Black towns, communities, institutions and places where history happened.
Moments that changed communities, movements, institutions and the nation.
In August 1908, a white mob attacked Springfield, Illinois’s Black community, destroying homes and businesses and lynching two Black men. National outrage over the violence helped spur the movement that created the NAACP the following year.
MORE →Reflects the personal views, recollections, and perspective of the author, Mike Davis.
This is a personal recollection on the Move fire on May 13, 1985
Fumitada Itakura (板倉 文忠, Itakura Fumitada; born 6 August 1940) is a Japanese scientist. He did pioneering work in statistical signal processing, and its application to speech analysis, synthesis and coding, including the development of the linear predictive coding (LPC) and line spectral pairs (LSP) methods.
Itakura was born in Toyokawa, Aichi Prefecture, Japan. He received undergraduate and graduate degrees from Nagoya University in 1963 and 1965, respectively.[1] In 1966, while studying his PhD at Nagoya, he developed the earliest concepts for what would later become known as linear predictive coding (LPC), along with Shuzo Saito from Nippon Telegraph and Telephone (NTT). They described an approach to automatic phoneme discrimination that involved the first maximum likelihood approach to speech coding.[2] In 1968, he joined the NTT Musashino Electrical Communication Laboratory in Tokyo.[1] The same year, Itakura and Saito presented the Itakura–Saito distance algorithm.[3] The following year, Itakura and Saito introduced partial correlation (PARCOR) to LPC.[2]
Itakura completed his D.Eng. degree in speech processing in 1972, writing his dissertation on "Speech Analysis and Synthesis based on a Statistical Method."[1] From 1973 to 1975, he worked at the Acoustics Research Department of Bell Labs, having been invited to work there on fundamental problems by James Flanagan, who had been impressed by one of Itakura's papers on low bit-rate encoding.[4]
In 1975, Itakura developed the line spectral pairs (LSP) method for high-compression speech coding, while at NTT.[5][6][1] From 1975 to 1981, he studied problems in speech analysis and synthesis based on the LSP method.[1] In 1980, his team developed an LSP-based speech synthesizer chip. LSP is an important technology for speech synthesis and coding, and in the 1990s was adopted by almost all international speech coding standards as an essential component, contributing to the enhancement of digital speech communication over mobile channels and the internet worldwide.[6]
In 1981, he was appointed as Chief of the Speech and Acoustics Research Section at NTT. He left this position in 1984 to take a professorship in communications theory and signal processing at Nagoya University. He currently teaches at Meijo University.[7]
Itakura's work on spectral and formant estimation laid the foundation for much of the early progress in speech signal processing.[8] His work on autoregressive modeling of speech is used in nearly every modern low-to-medium, bit-rate speech transmission system, and the line spectral pair representation he developed is now found in nearly all cellular telephone systems.[8]
His awards include the IEEE ASSP 1975 Senior Award, an award from Japan's Ministry of Science and Technology in 1977, the IEEE 1986 Morris N. Liebmann Award[9] (with B. S. Atal), the IEEE Signal Processing 1996 Society Award, the IEEE Third Millennium Medal, the IEICE 2002 Distinguished Achievement and Contributions Award, and the 2003 Purple Ribbon Medal from Japanese Government. In 2005, he received the Asahi Prize and the IEEE Jack S. Kilby Signal Processing Medal.[10][11] In 2009, he received the NEC C&C Prize for his pioneering research and the development of highly efficient voice-coding technology with analysis-synthesis methods for speech. He is a Fellow of the IEEE for pioneering contributions to speech processing,[12] and an honorary member the Institute of Electronics, Information and Communication Engineers of Japan.
{{cite web}}: CS1 maint: deprecated archival service (link)
| International | |
|---|---|
| National | |
| Academics | |
Source: Wikipedia. Article content is retrieved live through the MediaWiki API.
Fumitada Itakura (板倉 文忠, Itakura Fumitada; born 6 August 1940) is a Japanese scientist. He did pioneering work in statistical signal processing, and its application to speech analysis, synthesis and coding, including the development of the linear predictive coding (LPC) and line spectral pairs (LSP) methods.
The Itakura–Saito distance (or Itakura–Saito divergence) is a measure of the difference between an original spectrum P ( ω ) {\displaystyle P(\omega )} and an approximation P ^ ( ω ) {\displaystyle {\hat {P}}(\omega )} of that spectrum. Although it is not a perceptual measure, it is intended to reflect perceptual (dis)similarity. It was proposed by Fumitada Itakura and Shuzo Saito in the 1960s while they were with NTT. The distance is defined as: D I S ( P ( ω ) , P ^ ( ω ) ) = 1 2 π ∫ − π π [ P ( ω ) P ^ ( ω ) − log P ( ω ) P ^ ( ω ) − 1 ] d ω {\displaystyle D_{IS}(P(\omega ),{\hat {P}}(\omega ))={\frac {1}{2\pi }}\int _{-\pi }^{\pi }\left[{\frac {P(\omega )}{{\hat {P}}(\omega )}}-\log {\frac {P(\omega )}{{\hat {P}}(\omega )}}-1\right]\,d\omega } The Itakura–Saito distance is a Bregman divergence generated by the negative of the logarithmic function, but is not a true metric since it is not symmetric and it does not satisfy the triangle inequality. In Non-negative matrix factorization, the Itakura-Saito divergence can be used as a measure of the quality of the factorization: this implies a meaningful statistical model of the components and can be solved through an iterative method. The Itakura-Saito distance is the Bregman divergence associated with the Gamma exponential family where the information divergence of one distribution in the family from another element in the family is given by the Itakura-Saito divergence of the mean value of the first distribution from the mean value of the second distribution.
Line spectral pairs (LSP) or line spectral frequencies (LSF) are used to represent linear prediction coefficients (LPC) for transmission over a channel. LSPs have several properties (e.g. smaller sensitivity to quantization noise) that make them superior to direct quantization of LPCs. For this reason, LSPs are very useful in speech coding. LSP representation was developed by Fumitada Itakura, at Nippon Telegraph and Telephone (NTT) in 1975. From 1975 to 1981, he studied problems in speech analysis and synthesis based on the LSP method. In 1980, his team developed an LSP-based speech synthesizer chip. LSP is an important technology for speech synthesis and coding, and in the 1990s was adopted by almost all international speech coding standards as an essential component, contributing to the enhancement of digital speech communication over mobile channels and the internet worldwide. LSPs are used in the code-excited linear prediction (CELP) algorithm, developed by Bishnu S. Atal and Manfred R. Schroeder in 1985.
A timeline of events related to information theory, quantum information theory and statistical physics, data compression, error correcting codes and related subjects. 1872 – Ludwig Boltzmann presents his H-theorem, and with it the formula Σpi log pi for the entropy of a single gas particle 1878 – J. Willard Gibbs defines the Gibbs entropy: the probabilities in the entropy formula are now taken as probabilities of the state of the whole system 1924 – Harry Nyquist discusses quantifying "intelligence" and the speed at which it can be transmitted by a communication system 1927 – John von Neumann defines the von Neumann entropy, extending the Gibbs entropy to quantum mechanics 1928 – Ralph Hartley introduces Hartley information as the logarithm of the number of possible messages, with information being communicated when the receiver can distinguish one sequence of symbols from any other (regardless of any associated meaning) 1929 – Leó Szilárd analyses Maxwell's demon, showing how a Szilard engine can sometimes transform information into the extraction of useful work 1940 – Alan Turing introduces the deciban as a measure of information inferred about the German Enigma machine cypher settings by the Banburismus process 1944 – Claude Shannon's theory of information is substantially complete 1947 – Richard W. Hamming invents Hamming codes for error detection and correction (to protect patent rights, the result is not published until 1950) 1948 – Claude E. Shannon publishes A Mathematical Theory of Communication 1949 – Claude E. Shannon publishes Communication in the Presence of Noise – Nyquist–Shannon sampling theorem and Shannon–Hartley law 1949 – Claude E. Shannon's Communication Theory of Secrecy Systems is declassified 1949 – Robert M. Fano publishes Transmission of Information. M.I.T. Press, Cambridge, Massachusetts – Shannon–Fano coding 1949 – Leon G. Kraft discovers Kraft's inequality, which shows the limits of prefix codes 1949 – Marcel J. E. Golay introduces Golay codes for forward error correction 1950 – Richard Hamming publishes Hamming code paper, creates a new field of study Coding theory 1951 – Solomon Kullback and Richard Leibler introduce the Kullback–Leibler divergence 1951 – David A. Huffman invents Huffman encoding, a method of finding optimal prefix codes for lossless data compression 1953 – August Albert Sardinas and George W. Patterson devise the Sardinas–Patterson algorithm, a procedure to decide whether a given variable-length code is uniquely decodable 1954 – Irving S. Reed and David E. Muller propose Reed–Muller codes 1955 – Peter Elias introduces convolutional codes 1957 – Eugene Prange first discusses cyclic codes 1959 – Alexis Hocquenghem, and independently the next year Raj Chandra Bose and Dwijendra Kumar Ray-Chaudhuri, discover BCH codes 1960 – Irving S. Reed and Gustave Solomon propose Reed–Solomon codes 1962 – Robert G. Gallager proposes low-density parity-check codes; they are unused for 30 years due to technical limitations 1965 – Dave Forney discusses concatenated codes 1966 – Fumitada Itakura (Nagoya University) and Shuzo Saito (Nippon Telegraph and Telephone) develop linear predictive coding (LPC), a form of speech coding 1967 – Andrew Viterbi reveals the Viterbi algorithm, making decoding of convolutional codes practicable 1968 – Elwyn Berlekamp invents the Berlekamp–Massey algorithm; its application to decoding BCH and Reed–Solomon codes is pointed out by James L. Massey the following year 1968 – Chris Wallace and David M. Boulton publish the first of many papers on Minimum Message Length (MML) statistical and inductive inference 1970 – Valerii Denisovich Goppa introduces Goppa codes 1972 – Jørn Justesen proposes Justesen codes, an improvement of Reed–Solomon codes 1972 – Nasir Ahmed proposes the discrete cosine transform (DCT), which he develops with T. Natarajan and K. R. Rao in 1973; the DCT later became the most widely used lossy compression algorithm, the basis for multimedia formats such as JPEG, MPEG and MP3 1973 – David Slepian and Jack Wolf discover and prove the Slepian–Wolf coding limits for distributed source coding 1976 – Gottfried Ungerboeck gives the first paper on trellis modulation; a more detailed exposition in 1982 leads to a raising of analogue modem POTS speeds from 9.6 kbit/s to 33.6 kbit/s 1976 – Richard Pasco and Jorma J. Rissanen develop effective arithmetic coding techniques 1977 – Abraham Lempel and Jacob Ziv develop Lempel–Ziv compression (LZ77) 1982 – Valerii Denisovich Goppa introduces algebraic geometry codes 1989 – Phil Katz publishes the .zip format including DEFLATE (LZ77 + Huffman coding); later to become the most widely used archive container 1993 – Claude Berrou, Alain Glavieux and Punya Thitimajshima introduce Turbo codes 1994 – Michael Burrows and David Wheeler publish the Burrows–Wheeler transform, later to find use in bzip2 1995 – Benjamin Schumacher coins the term qubit and proves the quantum noiseless coding theorem 2003 – David J. C. MacKay shows the connection between information theory, inference and machine learning in his book. 2006 – Jarosław Duda introduces first Asymmetric numeral systems entropy coding: since 2014 popular replacement of Huffman and arithmetic coding in compressors like Facebook Zstandard, Apple LZFSE, CRAM or JPEG XL 2008 – Erdal Arıkan introduces polar codes, the first practical construction of codes that achieves capacity for a wide array of channels
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
MORE →Shirley Chisholm, elected in 1968.
