Mindket

Ahenk

Newversion 1 · updated

Overview

Reads Turkish text aloud in one designed synthetic female voice, with six emotions and laughter. It is a LoRA adapter for VoxCPM2 and needs a GPU.

Ahenk is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.

At a glance

You need
  • Python on your computer
  • A GPU
  • The VoxCPM2 base model from OpenBMB, which the adapter builds on
Runs in
  • A computer with a GPU, which the card requires
  • Python with the VoxCPM library, on Windows, macOS or Linux
  • Voice applications that speak Turkish
Start with
pip install -U huggingface_hub

Platform

WindowsOperating system
macOSOperating system
LinuxOperating system

About

What it is

Ahenk is a Turkish text-to-speech adapter for the VoxCPM2 model. It adds a LoRA of 36.2M parameters to a 2B base model and speaks in one designed female voice at 48 kHz. It can express six emotions and laughter. It needs a GPU.

Who it suits

It suits developers who need natural Turkish speech from a documented, openly licensed voice. The voice is synthetic and not any real person, so label what you generate as AI-generated.

IndustryWho uses itHow they use itExample
SoftwareTurkish-language app developersAdd spoken Turkish output to an appA voice assistant that reads replies aloud
Customer serviceSupport teamsVoice warm or empathetic repliesAn apology read in a caring tone
Content creationCreatorsNarrate Turkish scripts with a chosen moodA cheerful or calm voice-over
ResearchSpeech researchersStudy a LoRA adapter for expressive Turkish speechComparing the sample clips across emotions

People who need other languages or a clone of a real voice can skip it.

Where to use it

  • A computer with a GPU, which the card requires
  • Python with the VoxCPM library, on Windows, macOS or Linux
  • Voice applications that speak Turkish
Use caseWhoWhat they get back
NarrationCreatorsTurkish speech in a chosen mood
Support voiceCustomer service teamsCalm or empathetic spoken replies
Expressive linesApp developersLaughing, cheerful, sad or angry delivery

How to set it up

  • Python on your computer
  • A GPU
  • The VoxCPM2 base model from OpenBMB, which the adapter builds on
  1. Install the Hugging Face hub package.
  2. Download the adapter files.
  3. Load the VoxCPM2 base model and apply the adapter, following the model card.
pip install -U huggingface_hub
hf download ozgurguler/ahenk-tts-tr

How to use it

Give the model Turkish text. To set the mood, add a short English instruction in parentheses. The card's samples also run the text through a front end called trnorm, which spells out numbers and prices as words, and clean up pauses afterward. The text provided here has no run code.

(Cheerful and warm, smiling while speaking.)
(Calm, slow and soothing.)
ToolWhat it does
f022 voiceThe one designed female voice the adapter speaks in
Instruction in parenthesesSets the emotion, such as cheerful, calm, sad, angry or empathetic
trnorm front endRewrites numbers and prices as spoken words
pause_cleanTidies pauses after the speech is made

Example

You send a Turkish sentence with a price in digits, plus an instruction asking for a cheerful tone. The front end turns the price into words, and the voice reads the sentence warmly. The card's sample clips show this for several moods.

For newcomers and experts

A LoRA adapter is a small add-on that teaches a big model something new, here Turkish speech in a set voice. A first small step is to listen to the sample clips on the card, then try the same texts yourself.

The samples came from a published checkpoint with 16 sampling steps, a guidance value of 2.0 and seed 0 or 1. The card also notes the training voices were all AI-generated, and a smaller sibling, Ahenk Cep, can run in a browser.

  1. Turkish text plus an optional mood
  2. trnorm spells out numbers
  3. VoxCPM2 with the adapter makes speech
  4. Pauses are cleaned up

Good to know

  • License: CC BY 4.0 for the weights.
  • Cost to run: none named. You need a GPU of your own.
  • Data it reaches: it downloads files from the Hugging Face Hub, then turns your text into speech on your own machine.
  • Not for: passing the voice off as a real person. The card asks you to label output as AI-generated.
  • Turkish only, as the record lists.

README and files

README

Ahenk

Reads Turkish text aloud in one designed synthetic female voice, with six emotions and laughter. It is a LoRA adapter for VoxCPM2 and needs a GPU.

Made by ozgurguler on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

About

What it is: Ahenk is a Turkish text-to-speech adapter for the VoxCPM2 model. It adds a LoRA of 36.2M parameters to a 2B base model and speaks in one designed female voice at 48 kHz. It can express six emotions and laughter. It needs a GPU.

Who it suits: It suits developers who need natural Turkish speech from a documented, openly licensed voice. The voice is synthetic and not any real person, so label what you generate as AI-generated.

Industry | Who uses it | How they use it | Example
Software | Turkish-language app developers | Add spoken Turkish output to an app | A voice assistant that reads replies aloud
Customer service | Support teams | Voice warm or empathetic replies | An apology read in a caring tone
Content creation | Creators | Narrate Turkish scripts with a chosen mood | A cheerful or calm voice-over
Research | Speech researchers | Study a LoRA adapter for expressive Turkish speech | Comparing the sample clips across emotions

People who need other languages or a clone of a real voice can skip it.

Where to use it:

  • A computer with a GPU, which the card requires
  • Python with the VoxCPM library, on Windows, macOS or Linux
  • Voice applications that speak Turkish
Use case | Who | What they get back
Narration | Creators | Turkish speech in a chosen mood
Support voice | Customer service teams | Calm or empathetic spoken replies
Expressive lines | App developers | Laughing, cheerful, sad or angry delivery

How to set it up:

  • Python on your computer
  • A GPU
  • The VoxCPM2 base model from OpenBMB, which the adapter builds on
  1. Install the Hugging Face hub package.
  2. Download the adapter files.
  3. Load the VoxCPM2 base model and apply the adapter, following the model card.
pip install -U huggingface_hub
hf download ozgurguler/ahenk-tts-tr

How to use it: Give the model Turkish text. To set the mood, add a short English instruction in parentheses. The card's samples also run the text through a front end called trnorm, which spells out numbers and prices as words, and clean up pauses afterward. The text provided here has no run code.

(Cheerful and warm, smiling while speaking.)
(Calm, slow and soothing.)
Tool | What it does
f022 voice | The one designed female voice the adapter speaks in
Instruction in parentheses | Sets the emotion, such as cheerful, calm, sad, angry or empathetic
trnorm front end | Rewrites numbers and prices as spoken words
pause_clean | Tidies pauses after the speech is made

Example: You send a Turkish sentence with a price in digits, plus an instruction asking for a cheerful tone. The front end turns the price into words, and the voice reads the sentence warmly. The card's sample clips show this for several moods.

For newcomers and experts: A LoRA adapter is a small add-on that teaches a big model something new, here Turkish speech in a set voice. A first small step is to listen to the sample clips on the card, then try the same texts yourself.

The samples came from a published checkpoint with 16 sampling steps, a guidance value of 2.0 and seed 0 or 1. The card also notes the training voices were all AI-generated, and a smaller sibling, Ahenk Cep, can run in a browser.

Turkish text plus an optional mood
trnorm spells out numbers
VoxCPM2 with the adapter makes speech
Pauses are cleaned up

Good to know:

  • License: CC BY 4.0 for the weights.
  • Cost to run: none named. You need a GPU of your own.
  • Data it reaches: it downloads files from the Hugging Face Hub, then turns your text into speech on your own machine.
  • Not for: passing the voice off as a real person. The card asks you to label output as AI-generated.
  • Turkish only, as the record lists.

On Hugging Face, 13 November 2026

  • Task: text to speech
  • Library: voxcpm
  • Downloads in the last 30 days: 0
  • Likes: 29
  • License: cc-by-4.0
  • Languages: tr
  • Based on: openbmb/VoxCPM2
  • Tags: voxcpm, lora, turkish, synthetic-voice, designed-voice, emotional-tts, text-to-speech

Links

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download ozgurguler/ahenk-tts-tr

Then follow the usage in its model card. Nothing in this kit runs by itself.

Files
README.md  5 KB

1 file, 5 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-13

Compare with similar

Listed Hugging Face models in the same category that share the most tags with this one.

ProductDownloads, last 30 daysLikesParametersLicenseLast change
Ahenk This page029—cc-by-4.0
VoxCPM2Shares voxcpm · text-to-speech984,8601,7832.3Bapache-2.0
EMA LightningShares turkish · text-to-speech89,173461—apache-2.0
zipformer-asr-turkish-v1Shares turkish06—apache-2.0
MOSS-Image-SFT-4-stepsShares lora73,131965.1Bapache-2.0
Qwen3.5-4B-Claude-4.6-Opus-Reasoning-Distilled-GGUFShares lora39,9871884.2Bapache-2.0
Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13.

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