The article walks through using Step Plan’s unified API to integrate Claude Code for automated code review and to build a voice‑agent pipeline that transcribes meeting recordings, generates structured summaries, and produces audio briefs, while discussing setup, costs, model selection, practical demos, and observed limitations.
This article introduces RedditVideoMakerBot, an open‑source Python tool that automates fetching hot Reddit posts, creating TTS narration, adding background media, and producing a final video file without manual editing, and provides setup instructions and future feature ideas.
VoxCPM2, an open‑source 2‑billion‑parameter TTS model from OpenBMB, eliminates tokenizers and uses a diffusion‑autoregressive architecture to generate high‑fidelity, controllable speech in 30 languages, supporting voice design from natural‑language prompts and high‑quality voice cloning with just a short reference clip.
Kimi-Audio, a general‑purpose audio foundation model from Moonshot AI, integrates ASR, audio QA, automatic audio captioning, emotion classification and end‑to‑end speech dialogue within a single framework, detailing its mixed‑audio input, MiMo‑Transformer core, efficient synthesis pipeline, architectural strengths, limitations, and suitable application scenarios.
The article provides a comprehensive analysis of core voice interaction system capabilities—including barge‑in, turn‑taking, multi‑turn dialogue, intent recognition, speaker identification, streaming latency, noise robustness, multilingual support, emotion handling, personalization, security, and deployment considerations—highlighting typical scenarios such as smart speakers, in‑car assistants, call centers, and meeting transcription.
The article defines true speech large models as native end‑to‑end systems that directly map audio to audio, compares them with traditional cascade ASR‑LLM‑TTS pipelines across architecture, error control, latency, paralinguistic perception, long‑context handling and deployment, and surveys the leading open‑source and commercial speech LLMs released in March 2026 with a quick selection guide.
This article explains the technical distinction between intelligent speech— a toolbox of ASR, TTS, NLU, and NLG technologies— and Voice Agent, an end‑to‑end conversational system built on those tools and large‑model reasoning, illustrating their layered relationship, functional gaps, and typical use cases.
This article breaks down the end‑to‑end engineering pipeline that converts a knowledge source such as a URL or PDF into a narrated PPT‑style video, detailing six core stages—from knowledge extraction and script generation to image creation, voice synthesis, and final video stitching—while highlighting practical model choices, prompt design, and stability tricks.
NeuTTS‑Air, an open‑source on‑device text‑to‑speech model built on a 0.5B Qwen LLM and NeuCodec, reaches SOTA among open models, runs entirely on CPU, supports 3‑second voice cloning, and comes with a step‑by‑step tutorial for deployment on edge devices.
This guide walks you through building a Spring Boot application, registering a UnifiedTTS API key, configuring MiniMax or CosyVoice models, implementing the service layer, running unit tests, and handling production concerns to achieve high‑quality text‑to‑speech synthesis without changing client code.
This article explores how integrating ASR, TTS, and large language models into video conferencing creates an intelligent collaboration hub that boosts efficiency, enhances user experience, expands multilingual scenarios, and provides practical architecture and Python code examples for real‑time smart meetings.
This article examines how AI‑driven voice humanization—covering advanced ASR, intelligent interruption, and expressive TTS—addresses high labor costs, efficiency bottlenecks, and inconsistent service quality in inbound and outbound call‑center operations, presenting technical evaluations, optimization strategies, and future research directions.
This guide walks you through using the AI 易配音 long‑form audio tool to split a novel into chapters, assign distinct voice tones to each character, fine‑tune volume, speed and pitch, generate and batch‑process audio segments, and finally export the finished audio files.
This article details the end‑to‑end design of Taobao Live's AI digital human system, covering six core components such as LLM‑driven content creation, interactive dialogue, TTS voice synthesis, visual synchronization, audio‑video engineering, and a scalable backend, while also discussing product evolution, automation challenges, and future roadmap.
This article presents a comprehensive overview of the AI‑driven digital‑human live‑streaming solution used by Taobao, detailing six core components—including LLM‑based content generation and interaction, TTS, visual driving, audio‑video engineering, and backend services—while sharing architectural diagrams, cost‑reduction strategies, productization insights, and future directions.
This article details the end‑to‑end workflow for creating intelligent digital humans for live streaming, covering large‑language‑model‑driven content generation, multi‑stage TTS architecture, extensive audio‑signal processing, speaker clustering, front‑end text normalization, back‑end acoustic modeling, and quantitative evaluation of model improvements.
This article explains how Gaode Map leverages lightweight edge TTS models, dual‑autoregressive large‑model data augmentation, and a configurable audio‑processing DAG to enable users to create highly realistic personalized voice packs from just three recorded sentences.
This article reviews five free text‑to‑speech solutions—AI易视频, Google TTS, Natural Reader, Balabolka, and Speech2Go—detailing their features, language support, installation needs, and unique capabilities to help creators choose the right tool for narration, translation, or multi‑character audio production.
The article surveys Taobao’s AI‑generated audio pipeline, detailing eight technical papers on image‑to‑video, OpenAI o1, multimodal video, and large‑model voice synthesis, while highlighting advances like VALL‑E, CosyVoice, F5‑TTS, data‑cleaning methods, and e‑commerce applications such as voice‑cloned live streams, multilingual TTS, AI video‑audio integration, and audiobook production.
This article explains how to use NVIDIA Riva to rapidly deploy speech AI services, covering Riva's overview, Chinese ASR model updates, TTS capabilities, customization options, the Quickstart tool, and a Q&A session that clarifies deployment, model fine‑tuning, and integration with NeMo and Triton.
This guide explains the architecture of an interactive digital‑human system, walks through 3D avatar creation with Unreal Engine, details the AI controller that combines ASR, LLM and TTS, and provides step‑by‑step instructions for deploying the open‑source Fay project.
This article introduces NVIDIA’s open‑source NeMo framework, detailing its PyTorch‑based architecture for Speech AI, ASR and TTS training, NLP and LLM support, GPU‑optimized parallelism, pre‑trained model resources, fine‑tuning techniques, and the accompanying NeMo Aligner and Framework tools.
This article explains how to efficiently deploy speech AI models—including ASR and TTS—on GPUs using NVIDIA's Triton Inference Server and TensorRT, covering background challenges, GPU‑based solutions, decoding optimizations, Whisper acceleration with TensorRT‑LLM, streaming TTS improvements, voice‑cloning pipelines, future plans, and a Q&A session.
This article explores the concept of the metaverse and virtual humans, detailing 3D modeling techniques, NLP-driven language understanding, streaming TTS, VR/AR interaction, AIGC content generation, and the deployment of a large‑model intelligent Q&A system with real‑time facial expression synthesis for virtual anchors.
The article presents 58 Tongcheng AI Lab's AI sales assistant, detailing its background, a few‑shot voice‑cloning pipeline built on real dialogue data, data preprocessing, FastSpeech2‑based acoustic modeling, multi‑accent style transfer, deployment architecture, controllable synthesis parameters, and future research directions.
This article presents comprehensive best‑practice guidelines for deploying conversational speech AI—including ASR and TTS pipelines—on GPU servers using NVIDIA Triton Inference Server and TensorRT, covering workflow overview, performance optimizations, streaming inference, and real‑world deployment tips.
This article details Meituan’s adoption of the Media Resource Control Protocol (MRCP) to standardize ASR and TTS integration, describing its architecture, key components, high‑availability deployment, and measured performance gains such as up to 55% latency reduction and a 15% increase in outbound call success rates.
This article reviews Huawei Translation’s top-ranking results in the IWSLT 2022 speech translation competition across speech‑to‑speech, offline speech‑to‑text, and length‑controlled translation tasks, and details their cascade and end‑to‑end technical approaches, including domain‑controlled ASR, context‑aware MT re‑ranking, and VITS‑based TTS.
This article explains how Yuedu's TTS synthesis platform tackles the booming audiobook market by using AI‑driven text preprocessing, role graph construction, content structuring, emotion and effect recognition, and a streamlined post‑processing workflow to efficiently generate multi‑character, emotionally rich audio books at scale.
This article explains how an intelligent voice robot leverages TTS and SIP to convert server alerts into spoken notifications, detailing the end‑to‑end workflow, DTMF transmission methods, SIP detection techniques, SDP media negotiation, and RTP‑based DTMF parsing to enable reliable key‑press handling.
This article recounts the JD.com 11.11 tech salon presentation where architect Shi Weihang explains how the NeuHub gateway was redesigned to handle over two billion TTS service calls, detailing the challenges, scaling techniques, and architectural decisions that enabled such massive traffic.
This article explains the concept of full‑duplex natural dialogue for Alibaba’s Tmall Genie, illustrates interaction scenarios, and details the technical solution covering device‑side management, speech recognition, language understanding, synthesis, dialogue control, duration handling, and conversation flow.
This article introduces the architecture of smart speaker voice interaction systems, covering wake‑word activation, automatic speech recognition (ASR), natural language understanding (NLU), skill processing, text‑to‑speech synthesis (TTS), and the key performance and testing metrics for each component.
Tencent Cloud's intelligent speech platform combines high‑accuracy ASR, advanced WaveNet‑based TTS, and solutions for noise, far‑field, and dialect challenges, enabling voice input, transcription, and customer‑service bots, with real‑world deployments in finance, museums, hotels, and other industry scenarios.
The article surveys Tencent’s recent advances in smart‑speaker voice interaction, detailing a full technology chain—from front‑end capture, wake‑up and enhancement, through speaker verification and short‑speech voiceprint, to TDNN/LSTM speech recognition, target speaker extraction, and end‑to‑end attention modeling for robust, personalized performance.
This article explains how to enable voice reminders for payment receipt on iOS by using VoIP push notifications to wake a suspended app, integrating online/offline TTS synthesis, handling audio playback in background, detecting the mute switch, and adjusting system volume thresholds.
