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Voice Assistant

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DataFunTalk
DataFunTalk
Mar 15, 2024 · Artificial Intelligence

Application of Agent Technology in Voice Assistant Scenarios

Senior algorithm engineer Qi Jianwei from Xiaomi presents a comprehensive overview of building a large‑model‑centric Agent framework for voice assistants, covering prompt design, information retrieval, RAG processes, and future optimization directions to enhance performance and stability.

Voice Assistantagentinformation retrieval
0 likes · 2 min read
Application of Agent Technology in Voice Assistant Scenarios
DataFunSummit
DataFunSummit
Nov 20, 2022 · Artificial Intelligence

NLP Technology Applications and Research in Voice Assistants

This article presents an in‑depth overview of NLP techniques used in voice assistants, covering the end‑to‑end conversational AI pipeline, intent and slot modeling, multi‑turn dialog management, model deployment pipelines, quantization methods, and self‑learning strategies for continuous improvement.

Model QuantizationNLPVoice Assistant
0 likes · 30 min read
NLP Technology Applications and Research in Voice Assistants
DataFunTalk
DataFunTalk
Dec 28, 2021 · Artificial Intelligence

Evaluation Framework and Methodology for OPPO XiaoBu AI Assistant

This article presents a comprehensive evaluation framework for OPPO's XiaoBu AI assistant, covering evaluation concepts, objectives, five key elements, sampling methods, dimension selection, annotation scoring, report generation, and a detailed Q&A that illustrates practical metrics and processes for voice and search services.

AI evaluationOPPOVoice Assistant
0 likes · 23 min read
Evaluation Framework and Methodology for OPPO XiaoBu AI Assistant
DataFunSummit
DataFunSummit
Dec 27, 2021 · Artificial Intelligence

Evaluation Framework and Methodology for OPPO XiaoBu AI Assistant

This article presents a comprehensive evaluation framework for OPPO's XiaoBu AI assistant, covering the concept and purpose of evaluation, the five key evaluation elements, data sampling strategies, dimension and rule selection, annotation scoring, reporting guidelines, and detailed procedures for assessing wake‑up, ASR, NLU, and TTS performance.

AI evaluationAnnotationVoice Assistant
0 likes · 20 min read
Evaluation Framework and Methodology for OPPO XiaoBu AI Assistant
DataFunTalk
DataFunTalk
Nov 5, 2021 · Artificial Intelligence

End-to-End Entity Extraction for Tmall Genie: Speech2Slot Model and Unsupervised Pre‑Training

This article presents the business background of Tmall Genie’s voice‑driven content‑on‑demand service, critiques the traditional pipeline for entity extraction, and details an end‑to‑end speech‑semantic model—including the Speech2Slot architecture, knowledge‑enhanced encoding, and Phoneme‑BERT unsupervised pre‑training—demonstrating significant performance gains in both generation and classification tasks.

Speech RecognitionVoice Assistantend-to-end model
0 likes · 14 min read
End-to-End Entity Extraction for Tmall Genie: Speech2Slot Model and Unsupervised Pre‑Training
Java Architect Essentials
Java Architect Essentials
Oct 1, 2021 · Mobile Development

How to Quickly Access Health Code on iPhone and Android Devices

This guide explains step‑by‑step methods for iPhone and Android users to instantly open their health code using Siri shortcuts, double‑tap back gestures, home‑screen shortcuts, and voice assistants, improving efficiency during pandemic‑related checks.

AndroidHealth CodeMobile
0 likes · 5 min read
How to Quickly Access Health Code on iPhone and Android Devices
58 Tech
58 Tech
Jun 16, 2021 · Artificial Intelligence

Improving Text Matching Accuracy in Voice Assistants: Experiments with Siamese Networks, BERT Models, and Advanced Tricks

This article evaluates classic Siamese networks, various BERT‑based pretrained models, and several training tricks such as adversarial training, k‑fold cross‑validation, and model ensembling on both a public similarity‑sentence competition dataset and an internal voice‑assistant standard question matching dataset, ultimately raising accuracy from 97.23 % to 99.5 %.

BERTSiamese networkText Matching
0 likes · 15 min read
Improving Text Matching Accuracy in Voice Assistants: Experiments with Siamese Networks, BERT Models, and Advanced Tricks
Didi Tech
Didi Tech
Apr 29, 2021 · Artificial Intelligence

Design and Architecture of DiDi Driver-side Intelligent Voice Assistant "XiaoDi"

The document details DiDi’s driver‑side intelligent voice assistant “XiaoDi,” describing its three‑layer architecture—audio source switching controller, semantic‑parsing core, and business API—along with conflict‑resolution mechanisms, multi‑turn dialogue handling, and a four‑region UI design that together enhance driver safety, convenience, and well‑being.

AIDriver AppSpeech Recognition
0 likes · 30 min read
Design and Architecture of DiDi Driver-side Intelligent Voice Assistant "XiaoDi"
DataFunTalk
DataFunTalk
Feb 11, 2021 · Artificial Intelligence

How to Build Successful AI Products: Insights on AI Development, NLP, and Product Strategies

This article explores the current state of AI, the evolution of NLP and voice assistants, common pitfalls in AI product development, and practical product‑management methods—including user segmentation, metric design, and lifecycle planning—to help engineers and product managers deliver effective AI‑driven solutions.

AINLPVoice Assistant
0 likes · 19 min read
How to Build Successful AI Products: Insights on AI Development, NLP, and Product Strategies
DataFunTalk
DataFunTalk
Jul 26, 2018 · Artificial Intelligence

Natural Language Understanding in the Music Domain: Architecture, Features, and Challenges

The article details the design and implementation of Xiaomi's music‑focused natural language understanding platform, covering its service architecture, intent extraction, knowledge‑base search, slot filling, personalization, and the specific data and modeling challenges encountered.

ASRKnowledge BaseMusic
0 likes · 9 min read
Natural Language Understanding in the Music Domain: Architecture, Features, and Challenges
Hujiang Technology
Hujiang Technology
May 17, 2018 · Artificial Intelligence

Technical Analysis of Google Duplex: Achieving Natural Conversational Interaction

The article provides a detailed technical breakdown of Google Duplex, explaining how its speech recognition, natural language understanding, dialogue management, and speech synthesis modules work together to produce task‑oriented, natural‑sounding conversations and discussing challenges such as handling refusals, conditional responses, context management, and future scalability and safety concerns.

Artificial IntelligenceDialogue ManagementGoogle Duplex
0 likes · 10 min read
Technical Analysis of Google Duplex: Achieving Natural Conversational Interaction
AntTech
AntTech
May 10, 2018 · Artificial Intelligence

MISA – Ant Financial’s AI Voice Service Assistant: Architecture, Deep‑Learning Models, and the AI Competition

The article introduces MISA, Ant Financial’s AI‑driven voice service assistant that uses deep‑learning models such as CNN and RNN for problem guessing, identification, and interactive clarification, details its system components and evaluation metrics, and describes the related AI competition focused on sentence‑similarity calculation.

AINatural Language ProcessingVoice Assistant
0 likes · 14 min read
MISA – Ant Financial’s AI Voice Service Assistant: Architecture, Deep‑Learning Models, and the AI Competition
Liulishuo Tech Team
Liulishuo Tech Team
Dec 9, 2017 · Artificial Intelligence

Insights from AWS re:Invent 2017: Alexa, AI Challenges, and Voice Assistant Development

The author reflects on attending AWS re:Invent 2017, highlighting Alexa's AI capabilities, the ecosystem for skill development, the technical challenges of building voice assistants, and the need for tight integration of product, algorithm, and engineering to advance intelligent assistants.

AWSAlexaArtificial Intelligence
0 likes · 6 min read
Insights from AWS re:Invent 2017: Alexa, AI Challenges, and Voice Assistant Development