Luke Oliff is a Developer Relations leader based in the UK. For the better part of a decade he has been working with voice technology, developer tooling, and open-source, improving developer experience for well known brands. He has architected open-source strategy, launched developer communities, built tools, and shipped conversational AI voice prototypes years before mainstream APIs were available. As an engineer at heart, he writes and speaks about voice AI, developer experience, and real-time APIs as a developer would, focussing on utility and experience. He led Developer Relations for SpeechifyAI Build in 2026 and wrote these articles during his time on the team.
There's now a command line for Speechify. Install it from npm, log in with your API key, and synthesize speech, browse voices, and hand Speechify to your AI agent, all from your terminal.
Speechify's official LiveKit plugin streams word-level timestamps alongside the audio. Read them by overriding transcription_node and you get word-synced captions in a Python voice agent, with no extra API calls.
What streaming text-to-speech makes possible: read-aloud, voice agents, call narration, live captions, and read-along highlighting, all built on the Speechify streaming endpoints.
Give the Speechify text-to-speech API a URL and the page comes back as narrated audio. Fetch, extract the article text, chunk on sentence boundaries, synthesize each chunk with POST /v1/audio/speech.
What engineers actually use to add voice to web and mobile apps, and the four decisions that matter: the browser's built-in API versus a cloud one, streaming versus batch, where the key lives, and how to keep audio playing on iOS.
The tools for producing narration without hiring voice actors, compared on cost per finished hour rather than per seat. Studio subscriptions cap downloaded minutes; per-character APIs do not. One hour of audio runs from $0.31 to $40 depending on which you pick.
Which speech platform to pick when your chatbot has to talk. The decision is not voice quality, it is whether you need a TTS API or a full voice agent, plus how the model reads account numbers and order IDs back to a caller.
Generate the same script in English, German, Spanish, French, Italian, and Portuguese with the Speechify TTS API. Pick a simba-3.0 voice for each locale, call POST /v1/audio/speech per language, keep the key server-side.
How a Speechify provider for the AI SDK's generateSpeech() works: a dependency-free speech model that maps POST /v1/audio/speech onto SpeechModelV4, key held server-side in a Next.js route. Speechify now maintains one on npm, @speechify/ai-sdk-provider.
simba-3.2 is Speechify's streaming-native English TTS model, and GET /v1/audio/models lets you discover models at runtime instead of hardcoding a list. Since 21 October 2026 the recommended model is simba-3.5. What shipped, which voices 3.2 serves, and how to move.
Simba 3.2 for voice agents and narration at volume: 47 ms to first audible audio from US East on 9 October 2026, and $10 per 1M characters, $6 on Scale. Simba 3.5 (21 October 2026) speaks 48 languages with every catalog voice.
Clone a voice from a browser upload, synthesize speech with it, and keep your API key server-side. A working Next.js voice cloning app built on the Speechify API, no GPU required.
Point Deepgram Voice Agent at the open-source tts-shims OpenAI-compatible proxy to speak with a Speechify voice. The shim answers Deepgram's open_ai TTS request and keeps your Speechify key server-side.
Use SSML pauses, speaking rate, and pronunciation aliases to shape Speechify TTS output from one API request, and know which tags current models apply.
On the Artificial Analysis Speech Arena on 13 October 2026, Simba 3.2 scored 1,244 and was the lowest-priced model in the top ten, at $6.60 per million characters against $11 for the next. How the board's Elo works, and two independent latency readings.
Turn long-form ePub or Markdown into a single narrated chapter MP3 with a runnable Python demo: chunk on sentence boundaries, synthesize each chunk, stitch with ffmpeg.
How to stream audio from the Speechify TTS API in Python with plain HTTP and requests. Covers chunked streaming to disk and piping audio to a player without waiting for the full payload.
A practical guide to synthesizing speech in Node.js using the Speechify TTS API. Covers installation, a basic synthesis call, streaming audio to disk, and what to reach for next.
SpeechifyAI teamFirst published by Luke Oliff
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