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    <title>KAVANA Engineering Blog (English)</title>
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    <description>KAVANA Engineering Blog (English)</description>
    <language>en</language>
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      <title>What Actually Breaks in a Broadcast Audio Codec Pipeline (and How to Design Around It)</title>
      <link>https://www.kavanafm.com/blog/en/broadcast-audio-codec-pipeline.html</link>
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      <description>The phrase &quot;codec pipeline&quot; suggests a problem with a defined beginning and end: audio goes in one side, audio comes out the other, and the codecs are the boxes in between. In practice, a broadcast audio codec pipeline i</description>
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      <title>Engineering the Emergency-Broadcast Pipeline: When AI Radio Needs to Step Out of the Way</title>
      <link>https://www.kavanafm.com/blog/en/broadcast-emergency-broadcast-engineering.html</link>
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      <description>There is a class of broadcast engineering requirements where the consequences of failure are not a listener complaint or a regulatory annotation — they are a safety risk. Emergency broadcast is that class. When a nationa</description>
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      <title>Broadcast Loudness Normalization Without Tears: Getting BS.1770-4 Right Across a Multi-Station Deployment</title>
      <link>https://www.kavanafm.com/blog/en/broadcast-loudness-normalization-without-tears.html</link>
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      <description>Loudness normalization is one of those broadcast topics where the theory is well-documented and the practice is genuinely hard. The standards exist — BS.1770-4, EBU R 128, ATSC A/85, and a collection of national variants</description>
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      <title>Designing a Broadcast Overnight Music Rotation That Doesn&apos;t Sound Like a Playlist</title>
      <link>https://www.kavanafm.com/blog/en/broadcast-overnight-music-rotation-design.html</link>
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      <description>The overnight music block is one of those broadcast engineering problems that looks simple from the outside and becomes progressively harder the more carefully you think about it. The surface description is easy: play mu</description>
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      <title>Engineering perfect time calls and frequency IDs: the small details broadcast listeners notice when they go wrong</title>
      <link>https://www.kavanafm.com/blog/en/broadcast-time-call-and-frequency-id-engineering.html</link>
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      <description>There are two categories of on-air error that listeners notice immediately and remember long after the broadcast has ended. The first is a time call that is wrong — by a few seconds, by a minute, or simply by being absen</description>
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      <title>Treating broadcast traffic and weather updates as software engineering problems</title>
      <link>https://www.kavanafm.com/blog/en/broadcast-traffic-and-weather-as-software-engineering-problems.html</link>
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      <description>The public conversation about AI in broadcast tends to focus on the AI host: the voice, the style, the question of whether listeners can tell the difference. That is a reasonable thing to focus on if you are thinking abo</description>
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      <title>Engineering 24/7 Unattended Overnight Broadcast — What Actually Keeps the Station on Air at 4am</title>
      <link>https://www.kavanafm.com/blog/en/engineering-24-7-unattended-overnight-broadcast.html</link>
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      <description>For most of broadcast history, the answer to overnight coverage was simple: there was a person sitting in the studio. Not doing much, usually. Watching a playout system run, ready to press a button if something went wron</description>
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      <title>Engineering a Sub-Second Broadcast Failover That Actually Holds Up at 02:00 AM</title>
      <link>https://www.kavanafm.com/blog/en/engineering-a-sub-second-broadcast-failover.html</link>
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      <description>There is a particular kind of silence that broadcast engineers dread. It is not the silence of dead air — you can hear that immediately. It is the silence of a station that is technically on air, outputting carrier, but </description>
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      <title>Local GPU vs Public Cloud for Broadcast AI: the Math We Ran for 500 Stations</title>
      <link>https://www.kavanafm.com/blog/en/local-gpu-or-public-cloud-for-broadcast-ai.html</link>
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      <description>When we started having the local-versus-cloud conversation with stations in 2023, the standard advice from AI infrastructure consultants was unanimous: use the cloud. Marginal cost pricing, no upfront capital, elasticity</description>
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      <title>The Actual Cost of Dead Air: What 20 Years of Station Outages Taught Us About Broadcast Economics</title>
      <link>https://www.kavanafm.com/blog/en/the-actual-cost-of-dead-air.html</link>
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      <description>When broadcast engineers talk about dead air, they usually frame it as a technical failure. The playout machine crashed. The audio card locked up. The network path to the remote studio dropped. Something broke. The conve</description>
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      <title>The Three-Tier Content Review Pattern: Why One Approver Is Never Enough on Air</title>
      <link>https://www.kavanafm.com/blog/en/three-tier-content-review-pattern.html</link>
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      <description>A few years ago we watched a broadcast compliance incident unfold that had a straightforward cause: a single editor had approved a piece of content under deadline pressure, the editor was also the person who had written </description>
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      <title>What is a radio playout system? A 2026 buyer&apos;s guide for station engineers and program directors</title>
      <link>https://www.kavanafm.com/blog/en/what-is-radio-playout-system-2026.html</link>
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      <description>*Reading time: ~18 minutes. Audience: station engineers, program directors, and technology advisors who are evaluating or replacing broadcast automation software.*</description>
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      <title>When AI Hosts Hallucinate: Failure Modes We&apos;ve Seen and How Three-Tier Review Catches Them</title>
      <link>https://www.kavanafm.com/blog/en/when-ai-hosts-hallucinate.html</link>
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      <description>The word hallucination in AI discussions almost always refers to factual hallucination: a language model that confidently states something false. A chatbot that invents a court case. A research assistant that fabricates </description>
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      <title>Why a Broadcast-Grade AI Radio Host Isn&apos;t Just TTS in a Fancy Wrapper</title>
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      <description>Every few months someone sends us a link to a demo video: a radio station that has replaced its human DJ with an AI voice. The demo sounds impressive. The voice is natural, the transitions are smooth, the audio quality i</description>
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      <title>Why Broadcast Software Isn&apos;t SaaS: a 20-Year Operator&apos;s Perspective</title>
      <link>https://www.kavanafm.com/blog/en/why-broadcast-software-is-different-from-saas.html</link>
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      <description>Every few years the broadcast technology industry rediscovers the cloud. The pitch is consistent: move your broadcast automation to the cloud, eliminate on-premise hardware, pay per seat, scale elastically, let someone e</description>
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      <title>Why a 20-Year-Old Chinese Broadcast Software Team Is Opening to International Stations Now</title>
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      <description>We have been building broadcast automation software since 2005. In that time, we have shipped to more than 500 radio stations across China, survived the transition from tape to digital, watched the rise and fall of half </description>
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      <title>Why We Built Our Own Audio Firewall Format (wav9), and What It Actually Does</title>
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      <description>The broadcast content review process at a Chinese county-level station typically involves three human approval stages, a scheduling review, and a compliance sign-off before a segment is cleared for air. That review takes</description>
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