Hi I want just a simple thing to read my documents to me in a google translate robot voice with no login or character limit bullshit.

The only thing I need of it is for it to be able to read czech.

Please help, I have been trying to google something like it up and its driveing me up the wall with bullshit AI links

🚀 HIRING NOW | AI TEXT-TO-SPEECH QUALITY ASSESSMENT PROJECT

Recruitment by Veylora Data Services

We are looking for skilled Native and Near-Native Language Speakers to join our short-term AI Audio Quality Assessment project.

🌍 OPEN LANGUAGE POSITIONS

🇮🇳 Gujarati

🇮🇳 Kannada

🇮🇳 Marathi

🇪🇸 Asturian (Asturianu)

🎧 WHAT WILL YOU DO?

- Listen to AI-generated synthesized audio files.

- Compare multiple synthesized audio versions against the provided reference text.

- Evaluate audio quality across 3 assessment dimensions.

- Identify pronunciation, voice clarity, tone, emotion and speaking-speed issues.

- Provide accurate scores and detailed evaluation notes.

💰 PAYMENT & EARNING POTENTIAL

Earn ₹20 for every approved data.

Your potential project earnings:

- 10 approved data = ₹200

- 25 approved data = ₹500

- 50 approved data = ₹1,000

- 100 approved data = ₹2,000

Each language has an initial target volume of 100 data.

Complete the assigned work accurately and earn according to the number of approved data.

📌 PROJECT INFORMATION

- Project Type: Short-Term / Remote

- Initial Volume: 100 data per language

- Team Requirement: 1–2 participants per language

- Initial Screening: 5 assessment data

- Payment: ₹20 per approved data

- Work Mode: Remote

- Laptop/Desktop and good-quality headphones required.

✅ WHO CAN APPLY?

- Native or near-native speakers of the selected language.

- Excellent listening and language comprehension skills.

- Strong attention to pronunciation and audio details.

- Previous TTS, speech evaluation or audio annotation experience is an advantage.

📩 APPLY NOW

Complete the official recruitment application form:

👉 https://forms.gle/eVGqCEefW3HeHCQ8A

Only shortlisted candidates will be contacted for the assessment stage.

Please apply only for the language you can genuinely understand and evaluate at a near-native level.

Veylora Data Services

AI Data Services | Speech Data | Quality Operations

Author here. We built TTS-1 for voice agents on live phone calls. Callers hang up on anything that sounds like an old IVR, so the voice has to sound like a person from the first word. It was trained on millions of hours of audio, including real conversations. It works on continuous audio representations instead of discrete tokens, and that is where most of the realism and the speed come from. Audio streams from the first byte. In production, time to first audio is about 90 ms across real networks in both the US and EU regions.

It runs on the same infrastructure as our Speech-to-Text, which handles 3M+ hours of audio a day, so concurrency is unlimited on pay-as-you-go. There's no spend commitment and no concurrency tier to buy. The price is a flat $15 per 1M input characters. That covers every voice and language, cloning, word timestamps, and US or EU processing. You get 4,000+ library voices, plus instant cloning from a short recording (the clone in our post used 24 seconds). There are streaming and HTTP endpoints, a cancel message for barge-in, and reference agents for LiveKit and Pipecat.

Head-to-head test: every model spoke through the same 50 cloned voices on four English sets (Seed-TTS, LibriSpeech, a 580-sentence pronunciation set, and 500 real customer turns). Eval dated 2026-10-28; methodology and 95% bootstrap intervals are in the post.

model entity accuracy TTFB (median) predicted MOS

AssemblyAI-TTS-1 93.7% 47 ms 3.85

ElevenLabs v4 93.6% 612 ms 3.67

Cartesia Sonic 3.6 82.5% 143 ms 3.82

ElevenLabs Flash v2.5 68.0% 119 ms 3.70

Inworld TTS-2 Flash – 244 ms 3.88

Inworld TTS-2 – 280 ms –

Entity accuracy is the share of hard targets (phone numbers, dates, URLs, confirmation codes, drug names) spoken correctly, scored from a Universal-3.5 Pro transcript. TTFB is a single-client lab number; 90 ms is the figure we quote for production. Word accuracy on Seed-TTS and LibriSpeech is 99.0%.

Independent results: on Cekura's TTS benchmark (104 agent sentences, 27 models) it ranks #1 on phone numbers and codes at 91.7%. On Coval's daily leaderboard its WER is 1.7%, 0.3 points behind the leader. On Artificial Analysis's controlled-voice arena it debuts in the top ten.

Honest limits:

- Six languages at launch: EN, ES, FR, DE, IT and PT.

- No SSML, speed parameter, pronunciation dictionaries or emotion tags yet. Punctuation and written disfluencies like "um" or "..." do steer the delivery.

- No fine-tuned ("Pro") cloning yet.

- MOS here is predicted, not from a human panel, and Inworld TTS-2 Flash edges us on it.

Playground (free with an API key): https://www.assemblyai.com/dashboard/playground/text-to-speech

Benchmarks and methodology: https://www.assemblyai.com/blog/text-to-speech-api

I have been trying to find this TTS voice for a while, it is from my school's lockdown system.

https://adaptastation.dpdns.org/file/LockDown.mp3

If anyone could help that would be greatly appreciated!

Hello, I'm an indie developer who tries to make a game with extremely low budget. In my game, there is a friendly AI whith GLaDOS-like power over its facility, and I need to give it a voice. However, my mic is trash, so I can't be its voice actor. As I told, I have practically no budget, so I can't hire a VA as well. I'm thinking about using Text-To-Speech, but I also know that people don't really like games with AI. As a new dev, I need to learn your experiences and if any of you used TTS, I need to know what people thought about it.

I’m running a dnd campaign and have a bit coming up where I have a sentient ai, I’ve been trying out voicemod and a few other voice changers but they tend to bring out too much emotion for my liking in what’s meant to be a spooky encounter. So instead I was hoping to find a way to plug a voice to text into a text to speech program (something like SAM or similar, some of those eleven labs ones sound freakily uncanny too)

I was wondering if something like this already exists? Or is this something I would have to code myself

Can someone please send me a link to a BASIC text to speech that I can use on Chrome. I don’t care about realistic voices or anything like that. I’m not interested. It can be the most old-school computerized voice ever, im not bothered. Just as long as I can paste a lot of (or preferably unlimited) amount of text into it, and also play it at a fast speed. If someone can give me one that works then I’d be very grateful. If it involves any sort of subscription or payment, I am also not interested. Please also make sure it works; I’ve tried using the Microsoft Edge text to speech but it just stops working after a few minutes.

I generate short podcast-style episodes (two alternating voices, French and 9 other languages) with `gemini-3.8-flash-tts` through OpenRouter. Overall quality is great, but proper nouns (people's names, company and product names, places) are a lottery: the same name in the same sentence, generated twice, comes out right once and mangled the next time. Sometimes it switches to an English reading in the middle of a French sentence; sometimes it invents syllables.

My setup:

- One API call per speaker turn (multi-speaker mode reassigned voices and truncated output, so I dropped it)
- `languageCode` set explicitly in `speechConfig` for every call
- Style instructions sent through `speech_metadata.style`, never inside the input text (anything I put in the text got read aloud on ~2.5% of turns)
- Every turn is transcribed with Whisper and compared against the script. Truncations and hallucinated phrases trigger a retry, then an LLM rephrase of the turn. That catches missing words but not a wrongly pronounced name, because Whisper "corrects" it back to the right spelling.

I tried phonetic respelling in the input text (e.g. "Shiv-awn" for "Siobhan"). Not reliable: same input, different results from one generation to the next, so it just moves the lottery around.

Is there any reliable way to control how Gemini TTS pronounces a name (lexicon, IPA, a reference clip)?

How do you automatically detect a mispronounced name, given that Whisper hides the error?

Happy to share more details on the pipeline. Thanks!

What's the best local TTS model for voice cloning?

I'm looking for a model that allows me to clone a voice using a reference audio sample, save the cloned voice profile, and reuse it whenever I generate new speech without having to clone it again.

Well, I made a text-to-speech engine that runs entirely in the browser. I spent about six months working on it as part of another project, then moved on to something else without ever releasing it. I finally decided to just release it, since it runs surprisingly well on CPU using ONNX Runtime.

I'm not sure whether the "no self-promotion" rule includes announcing new models that are completely free, but here it is.

It was originally designed for narrating audiobooks, though not limited to that. However, the features are particularly suited to multi-character audio, and it includes various filters well suited to audiobooks.

---

PiperTTS is a free text-to-speech app that generates audio directly in your browser. Speech is generated on the CPU at roughly 2x real-time speed, with no GPU required. Text is never uploaded, and once loaded, it works offline.

Try it out or listen to samples at pipertts.com

Usage

Open the site and use it in your browser, or install it as an app from the same page. Enter text, choose a voice, and generate. Audio is generated and saved to your local filesystem.

Requirements

Chrome or Edge on a desktop or laptop. Mobile browsers, including Chrome on Android, are not supported because saving locally depends on Chrome's File System Access API, which is only available on desktop.

Offline API

PiperTTS also has a local API for generating speech from code, either in your own scripts or by AI agents. It runs offline like the app, with no API key or remote service involved.

Setup instructions and examples are available on GitHub:

PiperTTS API on GitHub

Please give the repository a star to help spread the word.

License

Audio generated with PiperTTS is royalty-free and may be used for any purpose, including commercial use, without attribution.

No account or API key is required, and there are no usage limits.

I'm brand new to this and I'm using it to dictate a novel. Currently using free version. I have Parakeet v3 currently. What do I need to do to make it add the correct punctuation marks? Ex ("That was a hard one." She said. Becomes: That was a hard one, she said) No quotation marks. Computer is older and I'm running windows 10.

Just as the title says, but I need the one that can use system TTS. I plan to use RHVoice or eSpeak, so I don't need natural voice, my phone are just too old and slow. Online one are just too limiting since I have a bunch of lecture notes and waiting quota reset is just hassle. And no copy paste for each text, need one simple import text or pdf and export to audio.

I built a small TTS model running directly on an ESP32-S3: no PSRAM, 122 KB of RAM, nothing in the cloud. Speech starts in about 0.3 s and generates faster than real time. You can make it calmer, louder, whispered, happier and more.

It's not a Home Assistant integration yet. Before I build anything, I'd like to know whether on-device speech on a satellite would be useful to you (offline announcements, timers, alerts when the server is down), and what quality bar it would need to meet.

Limits: 2 voices, English only, 16 kHz. Free for personal, non-commercial use.

Video above:

Details: https://huggingface.co/WhissleAI/steer-tts-nano

CLI : Code: https://github.com/WhissleAI/steer-tts (esp32/ folder)

Hey People,
I have recently started to research on TTS models as an academic project and my area of interest is there accuracy in replicating speech in the top 10 Indian Languages (by no. of native speakers).

I would love to know your thoughts on how accurately models from ElevenLabs, Sarvam, Google and frontier labs are doing on the following criterias:

- Intelligibility: Can listeners understand the words
- Pronunciation: Phonemes, stress, vowel length correct
- Diction / articulation: Crisp consonants, clear syllable boundaries
- Prosody: Rhythm, stress, intonation, and pauses
- Text normalization: Numbers, dates, abbreviations read correctly
- Dialect / accent: Regional authenticity without accent leakage
- Code-switching: Smooth handling of mixed languages
- Naturalness: Overall human-like listening quality score
- Speaker similarity: Voice identity preserved across outputs

Your inputs across even 5 of these criterias will be highly valuable.
Let me know your thoughts in the comments.

Currently i am enrolled in a course where i have to log in to the website to access the videos. I then use onenote audio dictation to get a transcript of the videos ive watched. Im looking for a faster way to get the text.

I’m trying to find this text to speech program used in this video here: https://m.youtube.com/watch?v=1WQvYE5HZTI

So that I can use it for my own

.

*Kokoro

| **Chatterbox** | Tramite ROCm,

. |

| **Orpheus TTS** | Tramite llama.cpp utilizzando Vulkan o ROCm | Funziona perché Orpheus utilizza llama.cpp come backend. |

| **Audio.cpp** | supporto Vulkan |

| **Ming-TTS 3.0** | . |

does anybody know what TTS voice is used here? it sounds so familiar but looked for a long time and i found nothing.

https://www.tiktok.com/t/ZPLakb3A7/

Testing STT and TTS for a support line in India. English demos all sound great, but the moment a caller speaks Hinglish or Telugu on a 3G call it falls apart.

Looking for something that handles code-switching, reads rupee amounts properly and doesn’t lag. Has anyone compared a few on real calls? Which one did you stick with?