Text to speech: how to evaluate synthesis quality
The "Text to speech" tool reads your text aloud with a browser-available voice or generates a synthetic eSpeak NG recording. This is not voice cloning and not studio dubbing. Quality depends on the chosen voice, language, and the text itself. In this guide we will break down how to objectively evaluate the result on a specific example, what parameters to check and what limitations to consider. You will learn to distinguish acceptable synthesis from unsuitable for your task.
Open tool: Text to speech ↗What the tool does exactly and what you get
You enter text (up to 3000 characters for speech synthesis) in the field "Your text or idea", select the output language and press "Generate". The output is audio in WAV format (eSpeak NG) or playback via a browser voice. The result appears in a separate panel and can be copied or downloaded as TXT, but not as an audio file. Important: if you need MP3 for a podcast, this tool is not suitable.
The tool does not perform automatic saving, does not support batch processing and does not have settings for timbre, speed or intonation. The only things you can control are the text and the language choice. Voices depend on the device: on one computer a set of voices may be available, on another — another. Therefore, quality assessment always starts with checking which voice was actually used.
eSpeak NG synthesis sounds robotic, but predictably. Browser voices may be more natural, but their presence and quality are not guaranteed. Neither option is photorealistic generation — this is speech synthesis, not recording of a live announcer.
Example: enter "Welcome to Iskra AI. Turn a small idea into something useful." Select English language. Press "Generate". Listen to the result.
Evaluation criteria: accuracy, completeness, intelligibility
Accuracy is correspondence of spoken words to the original text. Check that no words are omitted, endings are not replaced, numbers, abbreviations and proper names are read correctly. For example, "AI" may be read as "A-I" or "artificial intelligence" — depending on the voice. If an error distorts the meaning, the result is unsuitable.
Completeness is pronouncing the entire text without interruptions. Make sure the synthesis did not stop in the middle, did not swallow the last sentence and did not add unnecessary pauses breaking the phrase. This is especially noticeable on long sentences with commas and dashes.
Intelligibility is how easily a listener understands the speech without strain. A fast voice may "eat" syllables. Monotony is tiring. If understanding requires re-listening to a fragment, quality is low. Check at speed 1x and 1.5x — if speech becomes unintelligible when accelerated, this is a voice limitation, not a text limitation.
Take a phrase with numbers and abbreviations: "In 2025 the Research Institute launched 3 projects." Listen how "2025", "Research Institute" and "3" are pronounced. Write down errors.
Practical example: step-by-step check on a specific text
Suppose you want to dub a short greeting: "Welcome to Iskra AI. Turn a small idea into something useful." This is a fictional example for demonstration. Insert the text into the field, select English language, press "Generate". Listen to the result entirely, then by parts.
Step 1: check accuracy. Are all words in place? Is "Welcome" pronounced clearly? Is "Iskra AI" as "A-I" or "Iskra"? If "AI" sounds as "eye", that is normal for English. Step 2: check completeness. Are both sentences pronounced? Is there a pause after "AI" that breaks the meaning? Step 3: evaluate intelligibility. Is it understandable at first glance? If yes, the result can be used for a rough prototype.
Step 4: check suitability for your task. For background accompaniment of slides a robotic voice will do. For a commercial video — no. For an accessibility test — yes, if the speech is intelligible. Always ask: "Does this result solve my task?" If not, try another language or another voice if available.
After generation write down: accuracy — 100%, completeness — 100%, intelligibility — 7/10, suitability — only for internal prototype.
How to check the result objectively: checklist
Make a simple checklist of four items. 1) Accuracy: compare the audio with the original text word for word. 2) Completeness: make sure there are no omissions or interruptions. 3) Intelligibility: ask a colleague to listen and retell the meaning. 4) Suitability: does the voice match the purpose (training, background, prototype).
For checking accuracy it is convenient to enable subtitles if the tool creates them (SRT). But remember: subtitles may be generated separately and are not always synchronized with the speech. Better to verify by ear with a printed text. Mark every discrepancy.
If you test multiple voices, save results in separate TXT files with notes. Do not rely on memory: voices may sound similar but process numbers and pauses differently. Keep a log: date, language, voice, checklist evaluation.
Checklist: [ ] accuracy, [ ] completeness, [ ] intelligibility, [ ] suitability. Evaluation: 3 out of 4 — result requires text improvement.
Tool limitations and typical errors
The tool does not support voice cloning, does not generate video and does not create photorealistic images. This is speech synthesis only. Maximum text length for speech — 3000 characters. If text is longer, split it into parts and generate separately, but then pauses between fragments may be unnatural.
Browser voices depend on the operating system and installed language packs. On one device there may be 5 voices, on another — 1. If a voice is missing, the tool may switch to eSpeak NG or return an error. This is not a bug, but an environment limitation.
The model may err: put wrong stress, ignore punctuation, pronounce abbreviations letter by letter. The generation queue may be busy, and the result may not appear immediately. Do not use the tool for critical tasks without human listening.
Typical error: entering Russian text but selecting an English voice. Result — unintelligible pronunciation. Always check the selected language.
How to improve the result without changing the tool
Since there are no timbre and speed controls, the only lever is the text. Break long sentences into short ones. Replace abbreviations with full words: "AI" → "artificial intelligence", "НИИ" → "research institute". Write numbers in words: "2025" → "two thousand twenty-five". This increases accuracy.
Set punctuation for pauses. A period gives a longer pause than a comma. A dash may be ignored. Do not use special characters the voice cannot read. Check how every proper name is pronounced and if necessary replace with a phonetically simpler one.
If the voice sounds too fast, try adding periods at the end of meaning blocks. If monotone — vary sentence length. But remember: radically changing intonation is not possible. The tool is not designed for emotional dubbing.
Instead of "In 2025 the Research Institute launched 3 projects" write "In two thousand twenty-five the research institute launched three projects."
Evaluating speech synthesis quality is not about "liking/disliking", but about matching the task. Check accuracy, completeness, intelligibility and suitability on a specific example. Remember the limitations: dependence on device voices, no settings, maximum 3000 characters. The tool is suitable for rough prototypes, accessibility tests and background dubbing, but not for studio recording. Always listen to the result before use. If quality is insufficient, adapt the text, not expect a miracle from the tool.
Open tool: Text to speech ↗Interface translations are machine-assisted and may need refinement.