Language Technology for Social Good
Mitesh M. Khapra
Nilekani Centre at AI4Bharat, IIT Madras
मी तुम्हाला प्रतिकिलो 100 रुपये देऊ शकतो
100 கிலோ அரிசியை விற்க விரும்புகிறேன்
What would it take for a farmer in TN to talk to a wholesaler in Maharashtra?
We need to solve four fundamental problems
Speech Recognition
Language Understanding
Machine Translation
Speech Synthesis
Current setup
100s of calls daily in multiple languages manually answered by dedicated personnel
Challenges
Cannot scale effectively, some calls will not be answered, unnecessary repetition of work
How language technology can help?
Automatic processing of calls using speech and language technology
આજે બજારમાં મકાઈના ભાવ કેટલા છે?
Named Entity Recognition, Intent Identification, Natural Language Generation .....
Current setup
100s of books being translated manually into multiple languages (including Gondi, Santali, etc.)
Challenges
Requires skilled translators, lack of proper input and authoring tools
How language technology can help?
Good input tools, authoring tools and translation tools especially for under represented languages can help to achieve better scale
Transliteration, Translation, Spell check
santali
1.
2.
3.
Romanized keyboard
मक्का सुसतु झाला
I am tired
Konkani
Current setup
Surveys of 100s of families done manually in semi-urban and rural areas in multiple languages
Challenges
The process requires manual data entry which is time consuming and hence limits the number and length of surveys
How LT can help?
Record conversations and then use speech and language technology to extract entities and relations for automatic form-filling
माझ्या वडिलांना हृदयरोग झाला होता पण माझ्या आईला ते नव्हते
Information Extraction, Slot-filling
heart_condition (father, yes)
heart_condition (mother, no)
Commercial applications
Multilingual chatbots
Sentiment Analysis
Content Moderation
Code mixed song search
Speech
QA
Multilingual Authoring Tools
Confidential
By 2021 75% of Indian internet users will use Indian languages*
- 22 official languages
- 1.3 Billion speakers
Rich diversity
*Source Google-KPMG report https://assets.kpmg/content/dam/kpmg/in/pdf/2017/04/Indian-languages-Defining-Indias-Internet.pdf
Rich demand for speech and text technology
, growth
and demand
કેમ છો
कैसे हैं
Chat applications
Digital entertainment
Social media platforms
Digital
news
Digital write-ups
Digital payments
e-governance services
e-commerce services
Confidential
Why is this problem hard?
Open source all datasets and AI models with permissible licenses
Build a coalition of partners to collect datasets and deploy models
বা
हि
ಕ
म
ଓ
த
മ
తె
অ
कॉ
ગુ
ने
कों
सं
ਪੰ
सिं
اُر
ब
मै
Scale and Diversity
Unique language phenomenon
mujhe bahut confusion hai
Scarcity of resources
Lack of basic speech and NLP tools
Named Entity Recognition
Sentiment Analysis
Topic Classification
Content Filters
Keyboards
Spell checkers
Indian languages lag on academic benchmarks
Speech Recognition
Language Understanding
Machine Translation
Speech Synthesis
Summary: LT is foundational for the social sector?
Open source all datasets and AI models with permissible licenses
Build a coalition of partners to collect datasets and deploy models
Indian language + voice support =
Key to interface Bharat
Open source all datasets and AI models with permissible licenses
Build a coalition of partners to collect datasets and deploy models
Creating solutions based on local needs and behaviour is critical to improving user engagement
Consumer Survey,
Feb 2018, Bain Analysis
Voice could play a
pivotal role in enabling
e-governance and
bringing next 300 million
Indians to digital
platform
Nasscom Survey,
2019
Indian language users are expected to account for 75% of India' internet user base
KPMG/Google Survey,
2018
Chat & entertainment
Social media & news
Digital write-ups, payments, e-governance, e-commerce, search
Summary: LT can unlock commercial value?
What should we aim to do?
Bring parity with English
in AI tech for Indian languages
with open source contributions
Be the Apache for Indian languages AI stack
Have we solved parts of this problem?
Speech Recognition
Language Understanding
Machine Translation
Speech Synthesis
Mined 33 million
parallel sentences
Built billion parameter translation models
Our models for En to 11 Indian languages beat
all models (including
Google, Microsoft)
Who is using our translation models?
NGO for book translation
Govt. for website translation
Fiction book translation
Judgment
translation
Feedback from users
“The quality of translations is significantly improved. I would say this is more so for the legal document where there were complicated sentences/cards which were translated very well. The syntax mostly did not falter even in the face of multiple ideas/information contained in one sentence.”
“The amount of time spent on correcting/improving the translation has dropped.”
“THIS IS VERY PROMISING. AMAZED BY THE SPEED.”
“I TOOK A PRINTOUT AND WENT THROUGH EVERY LINE. THE TRANSLATION IS 98% ACCURATE AND HIGHLY SATISFIED.”
What should we do in the next 5 years?
Language Understanding
Machine Translation
Speech Synthesis
Speech Recognition
Create and release datasets
Train and open source AI models
Build deployable tools
Outreach to
drive use
Driving Science
Driving Adoption
Your Path to Language Technology
Python Packages
Prog. & Databases
Descriptive Statistics
Probability Theory
Inferential Statistics
Statistical Modelling
Functions
Calculus
Linear Algebra
Probability Theory (Adv.)
Optimisation
Machine Learning
Deep Learning
Pre-requisites
Foundations of DS
Foundations of ML
ML
DL
Information Theory
Language Technology
Associate Professor, IIT Madras
PhD, IIT Bombay
Mitesh M. Khapra
Pratyush Kumar
Anoop Kunchukuttan
Researcher, Microsoft Research
Adjunct Professor, IIT Madras
PhD, ETH Zürich
Researcher, Microsoft
PhD, IIT Bombay
100+ academic papers
30+ US patents
Recognized by
Experience
Team
Research expertise
