Short answer / recommendation
Choose a high-quality TTS specialist (my pick: ElevenLabs) for weekly 5–8 minute explainer videos when voice realism, multi-voice casting, batch/API automation and fine-grained editing are priorities. Use ChatGPT/OpenAI TTS as a lower-cost or integrated fallback if you already use OpenAI for scripting and want simpler plumbing.

Why (decision criteria)
- Voice naturalness & expressiveness: how close to a human, emotional range, intonation control (SSML or style tags).
- Multi-voice support & speaker switching: per-segment voice assignment and consistent character voices.
- Batch processing & API: bulk synthesis endpoints or straightforward programmatic queuing.
- Editing features: SSML support, word-level timestamps, phoneme overrides, pronunciation dictionary, prosody control, and easy trimming/format output.
- Cost model: per-minute vs per-character, subscriptions, rate limits.
- Workflow fit: how well it integrates into your script→record→edit pipeline and team size.

Practical recommendation
- Primary: ElevenLabs — excellent natural voices, expressive styles, multi-voice support, and a mature API that supports batching and fine-grained controls (SSML-like features, phoneme/pronunciation fixes). Good for creators where voice quality is top priority.
- Alternative/fallback: OpenAI/ChatGPT TTS — good if you already have automation around OpenAI and want fewer services to integrate; quality is strong but may be less customizable for character-style acting than a TTS specialist.

Pricing (ballpark — verify current docs)
- Expect roughly $0.10–$1.00 per finished audio minute for high-quality commercial voices depending on provider, voice tier, and whether you buy subscription bundles. Many providers price per characters (1 minute ≈ 150 words ≈ 900–1,000 characters), so convert before estimating.
- For production: run a short test batch to measure per-minute cost for the chosen voice and scale discounts.

Best-for / Avoid if
- Best for: creators who need broadcast-grade clarity, multiple distinct voices per episode, and full automation (batch API + post-processing). Teams who need predictable voice branding and easy iteration.
- Avoid if: you need lowest possible cost with synthetic-sounding voices, or if you require heavy live/real-time TTS (these services are better for pre-rendered narrated content).

Practical checklist to implement (quick, repeatable pipeline)
1) Finalize script and split into speaking segments (one voice per segment).
2) Tag segments with voice, SSML/prosody hints, and pronunciation overrides for proper nouns.
3) Write a small batch job that calls the TTS API (parallelize cautiously to avoid rate limits).
4) Request word-level timestamps to align subtitles and cuts.
5) Download and normalize audio (LUFS -16 for YouTube, 48kHz/24-bit if needed).
6) Apply light audio processing (denoise, EQ, compressor) in batch or DAW template.
7) Import aligned clips into your video editor, run a quick QA pass (listen for mispronunciations).
8) Re-generate only the corrected segments — avoid re-rendering the whole episode.

Notes about team/budget/workflow
- If you have an editor-only workflow, prioritize TTS with clear timestamps and per-clip files.
- If you have dev resources, choose a TTS provider with robust SDKs and bulk queuing so automation reduces per-episode labor.
- Budget: higher-tier expressive voices cost more but cut down on retakes and voice-actor fees.

If you want, I can outline a minimal Node/Python batch script that: reads a CSV of segments (text, voice, filename), calls the ElevenLabs API, downloads results, and writes a timeline-compatible manifest.

Compare options for ElevenLabs