Razvoj glasovnega asistenta

diplomsko delo

Urban Cör (Author), Marko Bajec (Mentor), Iztok Lebar Bajec (Co-mentor)

Abstract

Glasovni asistenti postajajo vse bolj priljubljeni in uporabni, vendar nobeden ne podpira slovenščine. Prav tako nismo odkrili pomočnikov, ki bi podpirali celoten cevovod glasovnega asistenta za slovenščino. V diplomskem delu smo razvili glasovnega asistenta za slovenski jezik za androidno napravo. Prepoznava ključne besede poteka lokalno na napravi, brez odvisnosti od interneta, s prilagojenim akustičnim modelom. Prepoznava govora poteka na zunanji storitvi z večjim akustičnim modelom. Za logiko glasovnega asistenta smo uporabili storitev Rasa, ki iz transkripcije uporabnikovega govora prepozna namen in kontekst. Odgovor te storitve se uporabi za sintezo odgovora, ki se nato predvaja uporabniku. Logiko na storitvi Rasa smo razširili, tako da ta storitev podpira tudi dva nova scenarija. Aplikacijo smo testirali v tihem okolju in v okolju s šumom za oba spola. Testirali pa smo tudi, delovanje aplikacije z uporabo druge storitve za transkripcijo govora. Aplikacija je najbolje delovala v tihem okolju za moškega govorca, saj v tem primeru ni prišlo do izpada iz toka delovanja aplikacije in smo čez celoten cevovod prišli v 100% testiranj. Primerljivo dobro pa je delovala tudi z uporabo druge storitve za transkripcijo govora, pri kateri smo čez celoten cevovod prišli v 94% testiranj.

Keywords

glasovno upravljanje;virtualni pomočnik;glasovni pomočnik;interdisciplinarni študij;univerzitetni študij;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2022
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[U. Cör]
UDC:	004.934.1(043.2)
COBISS:	102689283
Views:	507
Downloads:	91
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Development of the voice assistant
Secondary abstract:	Voice assistants are becoming more and more popular and useful. However, none of the best-known voice assistants support the Slovene language. We also have not found any assistants that would support the entire pipeline of the voice assistant for Slovene language. We have developed a voice assistant for Slovene language and for an Android device. Keyword detection is done locally on the device, without needing the Internet, and with a modified acoustic model. For speech recognition, we used an outside service with a bigger language model. For the logic of the voice assistant, we used Rasa. Rasa can detect the intent and context of the transcribed speech. The response from this service is used for speech synthesis and is then played back to the user. We tested the application in two different environments, silent and noisy, and for the male and female voice. We also tested if the application functions properly if we use another service for speech recognition. The application worked best in the silent environment for a male speaker. In that case we finished the pipeline in 100% of tests. We achieved comparable results when we used another service for speech recognition. We finished the pipeline in 94% of tests.
Secondary keywords:	voice control;virtual assistant;voice assistant;computer science;computer and information science;computer science and mathematics;interdisciplinary studies;diploma;Avtomatsko prepoznavanje govora;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS):	Bachelor thesis/paper
Study programme:	1000407
Embargo end date (OpenAIRE):	1970-01-01
Thesis comment:	Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages:	54 str.
ID:	14808607