Conversational AI Model Zoo

The purpose built models shipped with the TAO Toolkit - Conversational AI package can be used directly in tasks like answering questions across multiple domains, improving sentence semantics and more or can be re-trained or fine tuned to deploy a Conversational AI like a Virtual Assistant to service customers in varied fields like financial services, legal services, insurance, customer service and many more!

The table below shows the network architecture and the application area in which the model is trained. These models can be re-trained or fine tuned to change the domain/language according to the user’s requirements

Purpose Built Models for Conversational AI

Model Name

Base Architecture

Dataset

Purpose

Speech to Text English Jasper

Jasper

ASR Set 1.2 with Noisy (profiles: room reverb, echo, wind, keyboard, baby crying) - 7K hours

Speech Transcription

Speech to Text English QuartzNet

Quartznet

ASR Set 1.2

Speech Transcription

Speech to Text English CitriNet

CitriNet

ASR Set 1.4

Speech Transcription

Question Answering SQUAD2.0 Bert

BERT

SQuAD 2.0

Answering questions in SQuADv2.0, a reading comprehension dataset consisting of Wikipedia articles.

Question Answering SQUAD2.0 Bert - Large

BERT Large

SQuAD 2.0

Answering questions in SQuADv2.0, a reading comprehension dataset consisting of Wikipedia articles.

Question Answering SQUAD2.0 Megatron

Megatron

SQuAD 2.0

Answering questions in SQuADv2.0, a reading comprehension dataset consisting of Wikipedia articles.

Named Entity Recognition Bert

BERT

GMB (Gronigen Meaning Book)

Identifying entities in a given text (Supported Categories: Geographical Entity, Organization, Person , Geopolitical Entity, Time Indicator, Natural Phenomenon/Event)

Joint Intent and Slot Classification Bert

BERT

Proprietary

Classifying an intent and detecting all relevant slots (Entities) for this Intent in a query. Intent and slot names are usually task specific. This model recognizes weather related intents like weather, temperature, rainfall etc. and entities like place, time, unit of temperature etc. For a comprehensive list, please check the corresponding model card.

Punctuation and Capitalization Bert

BERT

Tatoeba sentences, Books from the Project Gutenberg that were used as part of the LibriSpeech corpus, Transcripts from Fisher English Training Speech

Add punctuation and capitalization to text.

Domain Classification English Bert

BERT

Proprietary

For domain classification of queries into the 4 supported domains: weather, meteorology, personality, and none.