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Fumitada Itakura

Fumitada Itakura is a astronomy topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Fumitada Itakura rather than just read about it. In short: 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.

Key takeaways

  • Fumitada Itakura belongs to astronomy; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Fumitada Itakura to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Fumitada Itakura from memory before moving on to harder problems.

Reference excerpt

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.

Biography Itakura was born in Toyokawa, Aichi Prefecture, Japan. He received undergraduate and graduate degrees from Nagoya University in 1963 and 1965, respectively. 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. In 1968, he joined the NTT Musashino Electrical Communication Laboratory in Tokyo. The same year, Itakura and Saito presented the Itakura–Saito distance algorithm. The following year, Itakura and Saito introduced partial correlation (PARCOR) to LPC. Itakura completed his D.Eng. degree in speech processing in 1972, writing his dissertation on "Speech Analysis and Synthesis based on a Statistical Method." 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. In 1975, Itakura developed the line spectral pairs (LSP) method for high-compression speech coding, while at NTT. 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. 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. Itakura's work on spectral and formant estimation laid the foundation for much of the early progress in speech signal processing. 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.

Awards 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 (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. 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, and an honorary member the Institute of Electronics, Information and Communication Engineers of Japan.

References

Worked examples

Example 1 — a first encounter with Fumitada Itakura

Start with the simplest possible case. Write down what Fumitada Itakura claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Fumitada Itakura before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Fumitada Itakura ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Fumitada Itakura

In research
Fumitada Itakura appears in astronomy research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Fumitada Itakura in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Fumitada Itakura is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1940 births, Academic staff of Nagoya University, Fellows of the IEEE, so understanding it makes those chapters shorter.
In everyday life
Look for Fumitada Itakura outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Fumitada Itakura in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Fumitada Itakura means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Fumitada Itakura out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Fumitada Itakura in simple terms?

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…

Why does Fumitada Itakura matter?

Because it connects several astronomy ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Fumitada Itakura?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Fumitada Itakura.

Tags

  • 1940 births
  • Academic staff of Nagoya University
  • Fellows of the IEEE
  • Living people
  • Nagoya University alumni
  • People from Toyokawa, Aichi
  • Scientists at Bell Labs
  • Speech processing researchers

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