Morgen Mukamwi provides a curriculum vitae summarizing his personal and academic details, skills, work experience, and references. He received a Bachelor of Engineering in Chemical Engineering from the National University of Science and Technology, and has work experience as a Chemical Engineering Intern at Unilever Zimbabwe and as a Sugar Packer at Tongaat Hulett Triangle. He is proficient in various engineering and computer skills, and seeks a challenging opportunity to utilize his skills and contribute to organizational success.
Closing the socio-economic gap in early literacy. Closing the skill maturity gap in early literacy. Closing the "way our brains work" gap in early literacy. By bringing universally available text-to-speech into early primary classrooms.
This document discusses text-to-speech (TTS) and speech recognition APIs available on Android. It describes how TTS is implemented using the TextToSpeech API and common methods like onInit. Speech recognition utilizes the RecognizerIntent to start the recognition activity and get results. Both APIs allow interacting with the user through voice instead of only touch interfaces.
Mapping the Personal Assistant
1. Speech Recognition/ NLP
2. Text-to-Speech/ NLP
Case Studies and Key Players
Text-to-Speech Deployment Models
1. Cloud Text-to-Speech
2. Embedded Text-to-Speech – HQ and HTS
Future of Personal Assistant, Mobile and Text-to-Speech
If you have any questions, please feel free to contact June Hostetter at June@neospeech.com.
When I learn more about Android's graphics system, and do more work about how to use CPU/GPU in more parallelized way to improve the graphics performance in Android,
I start to think that there are actually some big design mistakes in Android graphics system, especially the rendering architecture in the client side.Some mistakes have been solved after 3.x, especially above 4.1, but others can never be solved due to the compatible reason.
As developers, we need to know how the Android graphics system work, how to utilize the new features Android 3.x and 4.x provided, and how to do the optimization and overcome the shortage of Android.
Our speech to text conversion project aims to help the nearly 20% of people worldwide with disabilities by allowing them to control their computer and share information using only their voice. The system uses acoustic and language models with a speech engine to recognize speech and convert it to text. It can perform operations like opening calculator and wordpad. Speech recognition has applications in areas like cars, healthcare, education and daily life. Accuracy depends on factors like vocabulary size, speaker dependence, and speech type (isolated, continuous). The system aims to improve accessibility while reducing costs.
Morgen Mukamwi provides a curriculum vitae summarizing his personal and academic details, skills, work experience, and references. He received a Bachelor of Engineering in Chemical Engineering from the National University of Science and Technology, and has work experience as a Chemical Engineering Intern at Unilever Zimbabwe and as a Sugar Packer at Tongaat Hulett Triangle. He is proficient in various engineering and computer skills, and seeks a challenging opportunity to utilize his skills and contribute to organizational success.
Closing the socio-economic gap in early literacy. Closing the skill maturity gap in early literacy. Closing the "way our brains work" gap in early literacy. By bringing universally available text-to-speech into early primary classrooms.
This document discusses text-to-speech (TTS) and speech recognition APIs available on Android. It describes how TTS is implemented using the TextToSpeech API and common methods like onInit. Speech recognition utilizes the RecognizerIntent to start the recognition activity and get results. Both APIs allow interacting with the user through voice instead of only touch interfaces.
Mapping the Personal Assistant
1. Speech Recognition/ NLP
2. Text-to-Speech/ NLP
Case Studies and Key Players
Text-to-Speech Deployment Models
1. Cloud Text-to-Speech
2. Embedded Text-to-Speech – HQ and HTS
Future of Personal Assistant, Mobile and Text-to-Speech
If you have any questions, please feel free to contact June Hostetter at June@neospeech.com.
When I learn more about Android's graphics system, and do more work about how to use CPU/GPU in more parallelized way to improve the graphics performance in Android,
I start to think that there are actually some big design mistakes in Android graphics system, especially the rendering architecture in the client side.Some mistakes have been solved after 3.x, especially above 4.1, but others can never be solved due to the compatible reason.
As developers, we need to know how the Android graphics system work, how to utilize the new features Android 3.x and 4.x provided, and how to do the optimization and overcome the shortage of Android.
Our speech to text conversion project aims to help the nearly 20% of people worldwide with disabilities by allowing them to control their computer and share information using only their voice. The system uses acoustic and language models with a speech engine to recognize speech and convert it to text. It can perform operations like opening calculator and wordpad. Speech recognition has applications in areas like cars, healthcare, education and daily life. Accuracy depends on factors like vocabulary size, speaker dependence, and speech type (isolated, continuous). The system aims to improve accessibility while reducing costs.
快速生成FAQ Bot - 使用Azure Language Service LanguageService-03-FAQbot (微軟)(鐘祥仁)(20...AllenLi78
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This document is a presentation slide about how to create a FAQ bot using Azure AI services. It covers the following topics:
- The goal and overview of the FAQ bot project, which is to turn a company's FAQ page into a chatbot interface that can answer user queries.
- The Azure AI services involved in the project, such as Language Service, Custom Question Answering, and Azure Bot Service.
- The steps to build the FAQ bot, from creating a Language Service resource, importing the FAQ data set, deploying to Bot Service, and connecting to Line channel.
- The demo and summary of the FAQ bot project, showing how it works and what benefits it can bring.
Build local web server in 5 minutes with mongooserogeryi
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Mongoose is a small and lightweight web server that can be built and running in just 5 minutes, supporting Windows, MacOS and Linux. It includes features like CGI, SSL, SSI and supports HTTP requests like GET, POST, HEAD, PUT and DELETE. The entire Mongoose source code is under 40kb and is written in C. It can be downloaded from the project's Google Code page at http://code.google.com/p/mongoose.