Tag: Musio
Open Domain Dialogue Dataset Comparison Report
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
AKA’s paper is accepted by International Conference HIMS (Health Informatics and Medical System) //americancse.org/events/csce2020/conferences/hims20 (July, 2020)
Muse 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. […]
Musio’s High-Level Talks
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
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 […]
Evaluation for Muse Dialogue Engine 2019
Introduction Recent advances in AI has contributed to the rebirth of a chatbot-type dialogue system being able to interact with people through natural language communication. This could help people better understand the world around them and communicate more effectively with others, effectively bridging communication gaps. Therefore, it is important to understand the quality attributes associated developing and implementing high-quality conversational agents and diaglouge system. Muse is a NLP engine developed by AKA Intelligence, with a focus on natural conversation. Engineers at AKA and Softbank are collaborating to bring the Muse engine into Pepper, Softbank’s humannoid robot, to use Muse as Pepper’s English conversation system. Muse is also expanding into other hardware platforms as well. A typical example is Musio, a […]