AKA Story

Category: Musio

Open Domain Dialogue Dataset Comparison Report

Musio TeamA.I., Musio

Bach vs. Others This document presents a comparison between curated open-domain dialogue datasets available in the public domain and the data produced by AKA’s Bach data platform. The current report focuses on quantitative measurement which could be done in a transparent manner and represent objective differences found in the data. The analysis was performed using the following criteria: Total Number of Tokens Number of tokens is a measure of the overall size of the dataset. It is very important for training the modern Deep Learning-based models. Bach dataset displays clear superiority to others. Higher is better. Vocabulary Size Vocabulary size is the number of unique tokens appearing in the dataset. It represents the variety of speech in dialogues. Our dataset […]

AKA’s Paper (ReSmart) is accepted by HIMS 2020

Musio TeamA.I., Musio, Resmart

AKA’s paper is accepted by International Conference HIMS (Health Informatics and Medical System) //americancse.org/events/csce2020/conferences/hims20 (July, 2020)

Muse ReSmart

Musio TeamA.I., Musio, Resmart

As human beings live longer, the number of people diagnosed with dementia is growing. Many studies have proved that dementia tends to degenerate cognitive abilities. Since dementia patients endure different types of symptoms, it is important to monitor dementia patients individually. Furthermore, old people are generally lack of understanding technology, which brings a low self-motivation to use technologies.  To enhance the cognitive abilities of old people, we propose a mobile plat-form called ReSmart which embeds six distinct levels of the brain training task, based on five cognitive areas to detect different types of individual symptoms. Those brain training tasks are presented in a game-like format that aims to not lose the elder ‘s motivation for technology use and keeping interested. […]

Performance Evaluation of Bach’s Retrieval & Scoring System

Musio TeamA.I., Musio

Overview Most current applications of automated dialogue systems involve narrowly focused language understanding and simple models of dialogue interaction. Understanding language and generating natural dialogue are important in building friendly interfaces for dialogue system, but it is particularly critical in settings where the speaker is focused on 1D situation. Real human conversation is highly context-dependent, and human speakers jointly build contributions to the shared context. That is, human dialogue has a very complex structure by itself, and exhibits a complex network of relations between other dialogues. AKA has continuously tried to build friendly dialogue interfaces, and understand situation- and context-dependent interpretation of speaker utterances, including multiple situations. Bach, multiple linked dialogue data platform for AKA’s dialogue system, is our solution […]

Abusive Language Detection for Muse Engine

Musio TeamA.I., Musio

Overview Bach, multiple linked dialogue data platform for Muse engine, has utilized multiple resources – artificial intelligence, human reviewers, automated rating system, etc. – in an effort to generate best human-machine conversations, and a noisy data follows as a necessity from the development process. Noisy data is meaningless data, and its meaning can be expanded to include abusive language which causes challenges that we encountered when developing Muse engine. In this blog post, we will describe a development process of Muse engine ‘s abusive language detection system and demonstrate the efficacy by comparing the system with different models in detecting abusive language . To be brief, AKA’s abusive language detection system has shown a good performance by extracting additional features […]

Musio’s High-Level Talks

Musio TeamA.I., Musio

Introduction Producing sentences which are perceived as natural by a human is a crucial goal of all automated dialogue systems. It makes interactions more natural, avoids misunderstandings, and leads higher user satisifcation and user trust. However, making high-quality sentences constitutes hard challenges in terms of e.g., improving grammatical accuracy, or using a variety of sentences, or maintaining the context of conversation. Musio has explored a number of approaches to the task of high-quality sentence and is dedicated to making the step towards perfect dialogue system. In this blog post, we introduce the test results to show that Musio has its own peculiar methods to generate sentences and these are pretty well-formed sentences. Grammatical Correctness Musio always makes grammatically correct responses […]

Bach: data architecture for multi-linked dialogues

Musio TeamA.I., Musio

Introduction Dialogue systems are systems intended to converse with human users, and recent advancements in AI have contributed to closing the gap between human-machine conversations in many consumer services. AKA Intelligence researchers also tried to build automated dialogue systems and finally set up its own dialogue system, Muse, being able to practice English in addition to social conversations. One of the key differences between the existing systems and Muse is the customized data structure, Bach, to train AI model. It is important for recent dialogue systems to learn from human-human conversations in order to generate best human-machine conversations. Normally, the process of dialogue system may be summarized as follows: when a user asks a question, the system either searches a […]