Speech and Natural Language Processing
for Japanese Language
Prof. Dr. Satoshi Nakamura
Data Science Center,
Augmented Human Communication Lab,
Graduate School of Science and Technology

Nara Institute of Science and Technology

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Related Institutes in Japan
Ministry of Education, Culture, Sports, Science and Technology, Japan– National Institute of Informatics (NII)• Speech Corpus Consortium (SRC)– National Institute of Japanese Language and Linguistics (NINJAL)– Universities, including NAIST, U-Tokyo, U-Kyoto, Tokyo-tech, Nagoya-tech,..)– Related Associations: GSK (Gengo Shigen Kyokai: Language Resource Association)

Ministry of Economy, Trade, and Industry– National Institute of Advanced Industrial Science and Technology (AIST)• Artificial Intelligence Research Center (AIRC)

Ministry of Internal Affairs and Communications– National Institute of Information and Communications Technology (NICT)• ALAGIN (Advanced Language Information Forum)

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Speech Databases by NII-SRC
1. Priority Area Project on “Spoken Language” - Grant-in-Aid forDevelopmental Scientific Research on "Speech Database" Continuous Speech
Corpus (PASL-DSR)
2. University of Tsukuba Multilingual Speech Corpus (UT-ML)
3. Tohoku University - Matsushita Isolated Word Database (TMW)
4. GSR(A) “Regional Difference in Spoken Japanese Dialects” Spoken Japanese
Dialect Corpus (GSR-JD)
5. Real World Computing Project (RWCP) Speech Corpora
a.
b.
c.
d.

RWCP Spoken Dialogue Corpus - 1996 edition (RWCP-SP96)
RWCP Spoken Dialogue Corpus - 1997 edition (RWCP-SP97)
RWCP News Speech Corpus (RWCP-SP99)
RWCP Meeting Speech Corpus (RWCP-SP01)

6. RWCP Real Environment Speech and Acoustic Database (RWCP-SSD)
7. Priority Area “Spoken Dialogue” Spoken Dialogue Corpus (PASD)
8. CIAIR Children Voice Speech Corpus (CIAIR-VCV)
9. IPSJ SIG-SLP Corpora and Environments for Noisy Speech Recognition(CENSREC)
a.
b.
c.
d.

Noisy Speech Recognition Evaluation Environment (CENSREC-1/AURORA-2J)
Noisy Speech Detection Evaluation Environment (CENSREC-1-C)
Audio-Visual Speech Recognition Evaluation Environment (CENSREC-1-AV)
In-car Connected Digit Data and Environment for Noisy Speech Recognition(CENSREC-2)
e. In-car Isolated Word Data and Environment for Noisy Speech Recognition(CENSREC-3)
f. Reverberant Speech Recognition Evaluation Environment (CENSREC-4)

10. Priority Areas “Advanced Utilization of Multimedia to Promote Higher
Education Reform” Speech Database (UME)a. English Speech Database Read by Japanese Students (UME-ERJ)
b. Japanese Speech Database Read by Foreign Students (UME-JRF)

11. RIKEN Spoken Dialogue Corpus (RIKEN-DLG)

12. Chiba University Japanese Map Task Dialogue Corpus (MapTask)
13. Utsunomiya University Spoken Dialogue Database for Paralinguistic
Information Studies (UUDB)
14. Japanese Phonetically-balanced Word Speech Database (ETL-WD)
15. Speech Database of the 1991-1992 Tsuruoka Survey (Tsuruoka91-92)
16. X-ray Film database for speech research (X-Ray)
17. Priority Areas “Prosody and Speech Processing”
Japanese MULTEXT Prosodic Corpus (MULTEXT-J)
18. Chinese MULTEXT Corpus (MULTEXT-C)
19. Keio University Japanese Emotional Speech Database (Keio-ESD)
20. Vowel Database: Five Japanese Vowels of Males, Females, and Children
Along with Relevant Physical Data (JVPD)
21. Tokyo Institute of Technology Multilingual Speech Corpus (TITML)
a. Indonesian (TITML-IDN)
b. Icelandic (TITML-ISL)

22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.

AWA Long-Term Recording Speech Corpus (AWA-LTR)
Speech database of Aragusuku Dialect (Aragusuku)
Speech database of Oogami Dialect (Oogami)
Online Gaming Voice Chat Corpus with Emotional Label (OGVC)
Chiba Three-party Conversation Corpus (Chiba3Party)
Kinki University Japanese Isolated Word Database Read by Children (JWC)
ASJ Japanese Newspaper Article Sentences Read Speech Corpus (JNAS)Japanese Newspaper Article Sentences Read Speech Corpus of Aged
(S-JNAS)
ASJ Continuous Speech Corpus for Research (ASJ-JIPDEC)
NTT-Tohoku University Familiarity-controlled Word Lists (FW03)
NTT-Tohoku University Familiarity-controlled Word Lists 2007 (FW07)
NTT Infant Speech Database (INFANT)

3,721 Distributed in total
4
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Research Projects related to NII
Collection of elderly Japanese speech (Tokushima-u)
 Collection of multimodal dialog data (SIG-SLUD WG)


NTCIR
–
–

http://research.nii.ac.jp/ntcir/

A series of evaluation WS (18 months cycle) started in 1997
Each participants conducts experiments using the common data
• Information Retrieval (IR) , Question Answering (QA)
• Spoken Query and Spoken Document Retrieval, etc....

NTCIR-1

Term Extraction

NTCIR-2
NTCIR-3
NTCIR-4

NTCIR-5
NTCIR-6
NTCIR-7
NTCIR-8
NTCIR-9
NTCIR-10
NTCIR-11

Summarization

IR・Scientific・News paper
・WEB・GeoTime
・Spoken Doc・Medical Doc・Math・Recipe

MiningQA
Trend info
Visualization
Advanced QA

Entrance
Exam

NTCIR-12

Link
Discovery
Mobile IR

OpinionAnalysis

IntentMiningPatentRetrieval

PatentTranslation

MachineTranslation
Lifelog

NTCIR-13: Dec. 2017 => Lifelog, Medical doc, Entrance exam, Short text conversation, etc.
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Speech Databases and Software by NICT
Speech Databases
–
–
–
–
–
–
–
–

Japanese Aged Persons Speech Database
Non-native English Speech Database
Chinese Speech Database
Kyoto Sightseeing Information Dialog Database
Japanese Elementary School Pupils’ Speech Database
Japanese Speech Database
Japanese-English and Japanese-Chinese Monologue Speech Database
NICT Voice Actors Dialogue Corpus

Software– T3 Decoder
Individual members(ex. universities)

143

8 Corpora
1 Software
267 Distributed

124

100

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Regular members(ex. private companies)

FY2010 - FY2017

110

120

130

Digital revolution for under resourced languages in Asia 2019

140

150

http://www.naist.jp/

Research Projects related to NICT
Global Communication Plan
– Realization of High Quality Speech-to-Speech Translation– 5 year project funded by MIC (Ministry of Internal Affairs and Communications )1.38 billion yen in 2015
1.28 billion yen in 2016 and 2017
0.7 billion in 2018
– In 2020,
 Our technologies will be implemented as a“commonly-used” ICT device in shops,
stations, hospitals, hotels, and etc.
 10 languages (Japanese, English, Chinese,
Korean, Spanish, French, Thai, Indonesian,Vietnamese, Burmese) will be strongly supported.
– Our speech translation technology has been applied toseveral commercial services.

In Shops

In Stations

In Hospitals

In Hotels“ VoiceTra ”
Multilingual Speech Translation App
Example of collaboration
with NICT and private companies“ ili ”
Wearable Translation Device
released by Logbar Inc., 2017

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Other Research Projects in Japan
NAIST– JSPS S : “Next Generation Speech Translation” 2017-2021• Simultaneous Speech –to-speech Translation, Meeting Speech Translation

NINJALhttp://pj.ninjal.ac.jp/conversation/– Large-Scale Corpus of Everyday Japanese Conversation• Collection of conversations embedded in naturally occurring activities in daily life
• Collect more than 200 hours of recordings over six years
Recordings : 600-800 hours
Corpus : 200 hours (including transcriptions & automatically annotated tags)
Core Data : 20 hours (including manually annotated various tags)– Endangered Languages and Dialects in Japan

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http://kikigengo.ninjal.ac.jp/

Digital revolution for under resourced languages in Asia 2019http://www.naist.jp/

COCOSDA
International Committee for Coordination and Standardization of
Speech Databases
Workshops held annually at Interspeech, LREC
Cocosda promotes the development of spoken language corpora forbuilding and/or evaluating spoken language technology and offers
coordination of projects and research efforts to improve their efficiency.

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Necessity of Oriental COCOSDA

Asia is a multilingual region.

Diversity of the languages is larger than Europe.

Speech researches were emerging.

Speech corpora were required.



Cooperation among countries was necessary.



Organizations for speech corpora were needed.

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Organization of Oriental COCOSDAConvener: Satoshi NAKAMURA (2012-),Steering committee members:
Satoshi Nakamura (Japan), Shyam Agrawal (India), Aijun Li (China), Haizhou Li(Singapore), Luong Chi Mai (Vietnam), Chai Wutiwiwachai (Thailand), Yong-Ju Lee (South
Korea)



Ex-Conveners: Shuichi Itahashi (Japan), Chiu-yu Tseng (Taipei, China)Country Representatives: 26 from 13 regions including
China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, Mongolia,
Nepal, Singapore, Taiwan, Thailand, Vietnam, Myanmar

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History of Oriental COCOSDA (1)Year (Convener)
1998 (S. Itahashi)
1999
2000
2001
2002
2003
2004
2005
2006 (⇒C-Y. Tseng)
2007
2008
2009
2010
2011
(⇒S.Nakamura)
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Place, Country
Tsukuba, Japan
Taipei, Taiwan
Beijing, China
Daejon, Korea
Huahin, Thailand
Sentosa, Singapore
Delhi, India
Jakarta, Indonesia
Penang, Malaysia
Hanoi, Vietnam
Kyoto, Japan
Beijing, China
Kathmandu, Nepal
Hsinchu, Taiwan

HostS. Itahashi
L-S LeeHuang Tai-Yi
Y-J Lee
Virach Sornlertlamvanich
K-T Lua & Haizhou Li
S. Agrawal
H. Riza
Ambigapathy Pandian
L. C. Mai
S. Nakamura
T. Fang Zheng
B. N. Regmi
H-C Wang

Digital revolution for under resourced languages in Asia 2019http://www.naist.jp/

History of Oriental COCOSDA (2)Year (Convener)
2012 (S. Nakamura)
2013
2014
2015
2016
2017
2018
2019

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Place, Country
Macau, Chaina
Gurgaon, India
Phuket, Thailand

Host
T.Lee
S.S.Agrawal, P.K.Sexena
C. Wutiwiwaatchai,T.Theeramunkong,
M.Karnjanadecha
Shanghai, China
K.Hu, H.Ding
Bali, Indonesia
D.P.Lestari, A.Arman, H.Riza
Seoul, South Korea Y-J Lee, M.Chung
Miyazaki, Japan
S. Nakamura
Cebu, Philippines
N. OcoDigital revolution for under resourced languages in Asia 2019http://www.naist.jp/

Projects related to Oriental COCOSDA

A-Star:– Asia Language Speech Translation Advanced Research Consortium

AESOP:– Asian English Speech cOrpus Project

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Projects related to Oriental COCOSDA

A-Star:– Asia Language Speech Translation Advanced Research Consortium

AESOP:– Asian English Speech cOrpus Project

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Mechanism of speech translation system
Multilingual
SpeechRecognition

SpokenLanguageTranslation

Japanese「私は学校に行く: Watashi wa Gakko he iku」
w a t a sh i
w a g a xtu
k o o n i…..
Convert JapanesePhoneme sequence“a”,”I”,”u”,…

Watashi wa
Gakko he iku

Convert to word
sequencee
By lexicon andgrammer

I to school go

Convert Japanese word
sequence into English
word sequence
using dictionary

Multilingual
SpeechSynthesis
EnglishI go to school
I go to school

Re-order word sequence
According to English
grammer「私は:watashi ha」⇒ “I”「学校に:Gakko ni」⇒ “to school”「行く: iku」⇒“go”“I”“I”“to school”
“go”
“go”
“to school”

Large Scale Parallel
Corpora between
Japanese and English

Large Scale
English Text
CorporaSelect appropriate
waveform
to English text
from the corpus

CorporaLarge Scale
Japanese Speech
Corpora無限の可能性、ここが最先端 －Outgrow your limits－

Large Scale
Japanese Text
CorporaLarge Scale
English Speech
CorporaDigital revolution for under resourced languages in Asia 2019http://www.naist.jp/

Topics in BTEC Corpus
Spoken Language
Communication
Research Laboratories

Basic

TroubleShopping

Move

Stay

12.2% (7)12.1% (20)

10.0% (13)8.4% (8)8.2% (11)• greet someone• ask a question• state one’s
purpose•…

• luggage• emergency• medicine• assistance•…

• buy something• gather information• price• wrapping•…

• transportation• buy a ticket• rental car• trouble•…

• make/changea reservation• check-in• trouble•…

Study Overseas

1.6% (14)Sightseeing
7.7% (11)Restaurant
7.3% (11)Communication 6.4% (6)Airport5.5% (14)Business
5.3% (26)Contact
4.0% (6)
Airplane
3.6% (11)Homestay
2.3% (11)

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Drink
Exchange
Snack
BeautyGo HomeResearch

Digital revolution for under resourced languages in Asia 20191.3% (4)
1.2% (5)1.2% (4)0.8% (5)
0.6% (4)0.1% (12)http://www.naist.jp/

A-STAR: Asian Speech Translation ResearchConsortium (2006.6)

Spoken Language
Communication
Research Laboratories

 This project aims:
 Establishment of an international research collaborationgroup
 Building large scale speech and language corpora andtechnologies
 Initiate speech translation trial service in Asia Target languages:
Japanese, Chinese, Korean, Thai, Indonesian, Hindi, Malay,
Vietnam, …
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A-STAR Members

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Spoken Language
Communication
Research Laboratories

http://www.naist.jp/

A-STAR members
Spoken Language
Communication
Research Laboratories

EconomyInstitutions

Japan

Spoken Language Communication Res.Labs., ATR
National Institute of Information and Communications
Technology, NICT (Coordinator)

China

NLPR, Institute of Automation, Chinese Academy of Sciences,
CASIA

Chinese Taipei

National Taiwan University

Korea

Electronics and Telecommunications Research Institute, ETRI

Indonesia

Agency for the assessment and application of technology, BPPT

ThailandNational Electronics and Computer
Technology Center, NECTEC

India

CDAC, Center for Development ofAdvanced Computing, India+ Vietnam, Singapore (2008)
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Related Project: AESOPAsian English Speech cOrpus Project (since 2008)

International consortium of linguists, speech scientists,
psychologists and educators from Japan, Taiwan, Hong Kong,
China, Thailand, Indonesia, Mongolia, Myanmar to collect andcompare Asian English speech corpora in order to derive a setof core properties common to all varieties of Asian English andto discover features particular to individual varieties.

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NAIST Augmented Human Communication Lab
Brain
Analysis

Data Science
Center （2017-）
Incongruity measurement
Prediction of feelingProf.
Satoshi Nakamura

Assoc. Prof.
Katsuhito Sudo

Research
Assoc. Prof.
Sakriani Sakti

Assis. Prof.
Koichiro Yoshino

Research
Assoc. Prof.
Keiji Yasuda

Assis. Prof.
Hiroki Tanaka

Research
Assoc. Prof.
Yu Suzuki

Visiting Assoc.
Prof. Graham
Neubig (CMU)

Speech Translation
Neural MachineTranslation
Multi-language ASR
Speech Synthesis
Deep Speech Chain

Ｃ

Affective Computing
Emotion and Environment
Recognition
I’m looking fora lab.

Why don’t you
join our lab!

Early Detection of Dementia
Communication Support Dialog
Spoken Dialog
Multi-modal Dialog

WEB
Information
Processing
Goal-oriented Dialog
Non goal-oriented Dialog
Deep Neural
Network

Information
Retrieval
QA System
Multi-modal

NAIST
Bigdata
Project

Toward enhancement of human communication abilities
Toward enhancement of human communication abilities, AHC lab is studying multilingual speech translation, dialog system, useradaptive super-human automatic speech recognition/synthesis, and brain analysis related human communication. We have also been
managing Data Science Center since 2017 and Big Data Analytics Project since 2014.
/14

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JSPS Project:
Next Generation Speech Translation 2017-2021
Topic1: ASR and Speech Translation

Noise, Acoustics

Source Localization
Noise Reduction

Incremental Speech
Recognition ofMultiple Spleakers

Incremental
MT

Paralinguistic
Processing

Incremental
Paralinguistic MT

Incremental
Paralinguistic TTS
CaptionGeneration

Topic2: Palalinguistics
Speaking Face
Modeling,
Morphing

Incremental
TTS

Speaking Face
Conversion

Speaking Face
Synthesis

Topic3: Video Translation

Topic 4: Brain Sensing during Human
Communication
Gaze Detection, Heart Rate, 32ch EEG for
Measurement of Mental Loads
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Topic 5： Corpora and Prototype System
Collect more than 400 hours J-E Simultaneous Interpreterspeech corpora, and video translation corpora
Build Incremental Interpreting prototype system
Digital revolution for under resourced languages in Asia 2019http://www.naist.jp/

Human Interpreter Model[Mizuno 2016]
E-J Interpretation(1) The relief workers (2) say (3) they don’t have (4) enough food,water, shelter, and medical supplies (5) to deal with (6) the gigantic
wave of refugees (7) who are ransacking the countryside (8) in searchof the basics (9) to stay alive.
(1) 救援担当者は (9) 生きるための (8) 食料を求めて (7) 村を荒らし回っている (6) 大量の難民達の (5) 世話をするための (4) 十分な食料や水，宿泊施設，医療品が (3) 無いと (2)
言っています．

(1) 救援担当者達の (2) 話では (4)食料，水，
宿泊施設，医薬品が， (3) 足りず (6) 大量の難民達の (5) 世話が出来ないとのことです．
(7) 難民達は今村々を荒らし回って， (9) 生きるための (8) 食料を求めているのです．

Memory Chunk

Required Memory Chunk＞３！
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Required Memory Chunk ＜３！
Digital revolution for under resourced languages in Asia 2019http://www.naist.jp/

Thank you for listening

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History of Speech Translation Research In Japan
1986

1992

NAIST

1999

2006

2008

ATR

ATR

NICT

Read
SpeechDaily
Conversation

Wider andReal Domain+ More languages
for translation• Syntactically correct• Clear utterance• Limited domain
Ex. “Conference
Registration”• Standard expression• Unclear utterance• Limited domain
Ex. “Hotel Reservation”

ATR

2010

•21 multilateral text translation
VoiceTra• Wider and real domain“International Travel”
A-STAR• Realistic expressions• Noisy speech• J-E, J-C speech translation • Multilateral translation for 8 Asian languages• Network-based S2ST

2011

C-STAR

Fundamentals• Multilateral translation for 7 world languages

IWSLT• Evaluation Campaign of S2S technologies

Corpus-based Technology
Rule-based Technology
Hand-madeLarge scale corpus+ Machine learning

A-STAR
Asian Speech-to-Speech Translation
Research Consortium
Satoshi Nakamura1, Jun Park2, ChaiWutiwiwatchai3
Hammam Riza4, Karunesh Arora5, Chi Mai Luong6, Haizhou Li7
1National Institute of Information and Communications Technology (NICT), Japan¤
2Electronics and Telecommunications Research Institute (ETRI), Korea
3National Electronics and Computer Technology Center (NECTEC), Thailand
4Agency for the Assessment and Application of Technology (BPPT), Indonesia
5Center for Development of Advance Computing (CDAC), India
6Institute of Information Technology (IOIT), Vietnam
7Institute for Infocomm Research (I2R), Singapore

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Architectural Model
The architectural model assumed by this document has the following
components:
Speech translation client application
STML Interpreter

HTTP1.1

STML server
STML Interpreter

Web service
Application

Speech recognition

Speech Synthesis

Language Translation

A STML server processes context upon request from a client application, through the
STML Interpreters.
The server produces STML documents also in reply, which are processed by the STML
Interpreter.
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Expansion of Standardization technologies
 Network-based S2ST research by ASTAP consortium
2007

2006
Consortium

2010

2009

2008
A-STARU-STAR+Vietnam,Singapore

Japan, China, Korea,
Indonesia, Thailand, India

A-STAR
Network-based S2ST

 Standardization activity by ASTAP since 2008
ASTAP
Asia-Pacific Telecommunity
Standardization Program

SNLP EGStandardization on
Network-based S2ST

Transfer to
ITU-T Shift of standardization activity to ITU-T in 2009
ITU-T

SG16 Q21/Q22

International Telecommunication Union Telecommunication Standardization Sector

Initiation of Standardization on
Network-based S2ST

Digital revolution for under resourced languages in Asia 2019

Standardization activity of Network-based S2ST protocol
at ITU-SG16
 Activity start for standardization of Network-based S2ST at ITU-T SG16
 Session period：October, 2009 to the present
 NICT is the editor for S2ST standardization at ITU-T SG16, WP2 Q21/22
Document

F.745

H.625

Title

Scope
Functional Requirements for - Definition of Network-based S2ST
- Functions and service requirements of
Network-based S2ST
network-based S2ST
Architectural Requirements - Requirements of S2ST architecture- Definition of interface for Network-basedfor Network-based S2ST
S2ST

 Not only language conversion but also the potentially added module like sign
language are taken into account：
S2ST -> Modality conversion

Digital revolution for under resourced languages in Asia 2019

International Research Collaboration
A-STAR launched
Network-based
S2ST

2006

2007

2008

Consortium

2009

2011
U-STAR

A-STAR

Joins of Japan, China, Korea,
Indonesia, Thailand, India

2010+Vietnam,Singapore

7 institutes signed MOU ofU-STAR consortium

Currently, the participant members are 14 countries (15 institutes).

Digital revolution for under resourced languages in Asia 20198 institutes signed MOU ofU-STAR consortium