How to Automate Podcast Publishing With the Auphonic API
Auphonic has a REST API that turns a local WAV into a normalized MP3 with one POST. This covers the exact flow, the webhook callback…
Batch audio post-production with loudness targets, leveling and automatic transcriptions
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Pricing: free for 2 hours per month (files up to 2 hours each). Paid tiers scale by processing hours — roughly $11 for 9 hours, $22 for 20 hours, $44 for 42 hours per month. Speech recognition is metered separately as credits. A weekly hour-long show needs about 4-5 hours monthly, so the entry paid tier is enough for most independent podcasters.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Pricing: free for 2 hours per month (files up to 2 hours each). Paid tiers scale by processing hours — roughly $11 for 9 hours, $22 for 20 hours, $44 for 42 hours per month. Speech recognition is metered separately as credits. A weekly hour-long show needs about 4-5 hours monthly, so the entry paid tier is enough for most independent podcasters.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Pricing: free for 2 hours per month (files up to 2 hours each). Paid tiers scale by processing hours — roughly $11 for 9 hours, $22 for 20 hours, $44 for 42 hours per month. Speech recognition is metered separately as credits. A weekly hour-long show needs about 4-5 hours monthly, so the entry paid tier is enough for most independent podcasters.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Pricing: free for 2 hours per month (files up to 2 hours each). Paid tiers scale by processing hours — roughly $11 for 9 hours, $22 for 20 hours, $44 for 42 hours per month. Speech recognition is metered separately as credits. A weekly hour-long show needs about 4-5 hours monthly, so the entry paid tier is enough for most independent podcasters.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
That heritage matters. It is not a generative model inventing a new voice; it is a competent engineer’s preset applied consistently. Episodes come out at a consistent volume week to week, which is more than most podcasters manage by hand in Audacity.
Pricing: free for 2 hours per month (files up to 2 hours each). Paid tiers scale by processing hours — roughly $11 for 9 hours, $22 for 20 hours, $44 for 42 hours per month. Speech recognition is metered separately as credits. A weekly hour-long show needs about 4-5 hours monthly, so the entry paid tier is enough for most independent podcasters.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
That heritage matters. It is not a generative model inventing a new voice; it is a competent engineer’s preset applied consistently. Episodes come out at a consistent volume week to week, which is more than most podcasters manage by hand in Audacity.
Pricing: free for 2 hours per month (files up to 2 hours each). Paid tiers scale by processing hours — roughly $11 for 9 hours, $22 for 20 hours, $44 for 42 hours per month. Speech recognition is metered separately as credits. A weekly hour-long show needs about 4-5 hours monthly, so the entry paid tier is enough for most independent podcasters.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Auphonic was built in Austria by Georg Holzmann, an audio engineer, and launched in 2011. It predates the modern AI-podcast wave by a decade — its automation is signal processing first (loudness, adaptivity, noise reduction) with speech recognition bolted on later.
That heritage matters. It is not a generative model inventing a new voice; it is a competent engineer’s preset applied consistently. Episodes come out at a consistent volume week to week, which is more than most podcasters manage by hand in Audacity.
Pricing: free for 2 hours per month (files up to 2 hours each). Paid tiers scale by processing hours — roughly $11 for 9 hours, $22 for 20 hours, $44 for 42 hours per month. Speech recognition is metered separately as credits. A weekly hour-long show needs about 4-5 hours monthly, so the entry paid tier is enough for most independent podcasters.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.
Auphonic is automated audio post-production for spoken content. Upload a multitrack recording and it levels speakers, removes noise hum, normalises to a target loudness (e.g. -16 LUFS for podcasts, -23 LUFS for EBU broadcast) and exports MP3 with ID3 tags. Free accounts get 2 hours of processing per month.
Auphonic was built in Austria by Georg Holzmann, an audio engineer, and launched in 2011. It predates the modern AI-podcast wave by a decade — its automation is signal processing first (loudness, adaptivity, noise reduction) with speech recognition bolted on later.
That heritage matters. It is not a generative model inventing a new voice; it is a competent engineer’s preset applied consistently. Episodes come out at a consistent volume week to week, which is more than most podcasters manage by hand in Audacity.
Pricing: free for 2 hours per month (files up to 2 hours each). Paid tiers scale by processing hours — roughly $11 for 9 hours, $22 for 20 hours, $44 for 42 hours per month. Speech recognition is metered separately as credits. A weekly hour-long show needs about 4-5 hours monthly, so the entry paid tier is enough for most independent podcasters.
Two features quietly justify the subscription. First, Multi-level filters: you stack leveling, normalize, denoise and cut filters in order and save the chain as a preset. Second, the API and watch folders — point Auphonic at a Dropbox folder and every new file is processed and published automatically. For a producer shipping three shows a week, that removes a manual step entirely.
Transcription accuracy is good on clean English, mediocre on accented audio and heavy crosstalk. It is included because it is useful for show notes, not because it competes with dedicated ASR APIs.
It is a batch processor, not an editor. You cannot cut out a rambling anecdote inside Auphonic — you edit first in Descript, Audacity or Reaper, then send the result for processing. The interface looks like 2015 and the per-file upload flow is slower than a local app.
Aggressive noise reduction adds a slight underwater artifact on quiet passages. And its denoise is not in the same league as Adobe Podcast’s Enhance Speech for genuinely bad recordings — different jobs. Auphonic is for consistency across many good-enough episodes; Adobe is for rescuing one bad file.