{"product_id":"waves-forensics-package-399487","title":"Forensics Package","description":"\u003ch3\u003eWhat Waves Forensics Package Is Used For\u003c\/h3\u003e\u003cp\u003eWaves Forensics Package is a collection of audio plugins designed for the demanding needs of \u003cstrong\u003eforensic audio\u003c\/strong\u003e: exploiting low-quality recordings, revealing information masked by noise, and \u003cstrong\u003erestoring\u003c\/strong\u003e takes from imperfect sources (phones, walkie-talkies, hidden microphones, cameras, portable recorders). It is intended for audio laboratories, technicians working on sensitive cases, as well as editors and sound engineers who need to clean voices and complex environments while maintaining a natural and usable result.\u003c\/p\u003e\u003ch3\u003eMain Features\u003c\/h3\u003e\u003ch4\u003eA suite developed with a field specialist\u003c\/h4\u003e\u003cp\u003eThe package was designed in collaboration with international forensic audio expert \u003cstrong\u003ePhil Manchester\u003c\/strong\u003e, with a clear focus: to provide comprehensive tools to handle \"difficult\" recordings, where a classic restoration chain shows its limits.\u003c\/p\u003e\u003ch4\u003ePrecision equalization to isolate information\u003c\/h4\u003e\u003cp\u003eThe \u003cstrong\u003e10-band\u003c\/strong\u003e equalizer allows precise targeting of problematic frequency areas or, conversely, boosting useful bands (notably for \u003cstrong\u003espeech intelligibility\u003c\/strong\u003e). This approach helps focus listening on key elements, reduce masking, and prepare the signal before noise reduction processing.\u003c\/p\u003e\u003ch4\u003eMultiband noise reduction and spectral noise reduction\u003c\/h4\u003e\u003cp\u003eFor intrusive ambiances (hiss, ventilation, traffic, background murmur), the \u003cstrong\u003emultiband noise reduction\u003c\/strong\u003e enables a more musical and controlled action depending on frequency zones. The \u003cstrong\u003espectral noise reduction\u003c\/strong\u003e identifies unwanted components to remove them with greater precision, useful when noise is irregular or when certain disturbances appear intermittently.\u003c\/p\u003e\u003ch4\u003eArtifact and recording defect removal\u003c\/h4\u003e\u003cp\u003eLow fidelity recordings can accumulate mechanical and electrical defects. The suite offers processing to \u003cstrong\u003ereduce\u003c\/strong\u003e clicks, pops, crackles, and \u003cstrong\u003ehum\u003c\/strong\u003e to clean the signal before analysis or transcription and limit listening fatigue during long sessions.\u003c\/p\u003e\u003ch4\u003eDynamic processing to bring out details\u003c\/h4\u003e\u003cp\u003eDynamic processors (including \u003cstrong\u003ecompression\u003c\/strong\u003e) help highlight weak sounds and buried information while maintaining control over peaks and sudden variations. The goal is to gain presence and clarity, especially on distant voices or those recorded in noisy environments.\u003c\/p\u003e\u003ch4\u003eAnalysis and problem detection\u003c\/h4\u003e\u003cp\u003eThe \u003cstrong\u003ePAZ Analyzer\u003c\/strong\u003e facilitates the identification of artifacts and similar anomalies to locate areas to treat faster and objectify restoration choices. Coupled with \u003cstrong\u003ereal-time\u003c\/strong\u003e operation, it supports an efficient workflow from diagnosis to final output.\u003c\/p\u003e\n\n\u003ch2\u003eTechnical specifications\u003c\/h2\u003e\n\u003cstyle\u003e@media(max-width:632px){table[data-wb-spec]{display:grid;grid-template-columns:minmax(0,1fr) minmax(0,1fr)}table[data-wb-spec] colgroup{display:none}table[data-wb-spec] tbody,table[data-wb-spec] tr{display:contents}table[data-wb-spec] td{display:block;overflow-wrap:anywhere;grid-row:var(--wb-l);background-color:var(--wb-lb)}table[data-wb-spec] td[data-r]{grid-row:var(--wb-r);background-color:var(--wb-rb)}table[data-wb-spec] td[colspan=\"2\"]{grid-column:1\/-1}table[data-wb-spec] td:empty{display:none}}\u003c\/style\u003e\n\u003ctable data-wb-spec style=\"width:100%;table-layout:fixed\"\u003e\n\u003ccolgroup\u003e\u003ccol style=\"width:25%\"\u003e\u003ccol style=\"width:25%\"\u003e\u003ccol style=\"width:25%\"\u003e\u003ccol style=\"width:25%\"\u003e\u003c\/colgroup\u003e\n  \u003ctr style=\"background-color:var(--wb-neutral-50);--wb-l:1;--wb-r:2;--wb-lb:var(--wb-neutral-50);--wb-rb:transparent\"\u003e\u003ctd style=\"text-align:left\"\u003e\u003cstrong\u003eType\u003c\/strong\u003e\u003c\/td\u003e\u003ctd style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003eFull software\u003c\/td\u003e\u003ctd data-r style=\"text-align:left\"\u003e\u003cstrong\u003eDownloadable\u003c\/strong\u003e\u003c\/td\u003e\u003ctd data-r style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003eYes\u003c\/td\u003e\u003c\/tr\u003e\n\u003c\/table\u003e\n\u003ctable data-wb-spec style=\"width:100%;table-layout:fixed\"\u003e\n\u003ccolgroup\u003e\u003ccol style=\"width:25%\"\u003e\u003ccol style=\"width:25%\"\u003e\u003ccol style=\"width:25%\"\u003e\u003ccol style=\"width:25%\"\u003e\u003c\/colgroup\u003e\n  \u003ctr style=\"background-color:transparent;--wb-l:1;--wb-r:5;--wb-lb:var(--wb-neutral-50);--wb-rb:var(--wb-neutral-50)\"\u003e\u003ctd style=\"text-align:left\"\u003e\u003cstrong\u003emacOS\u003c\/strong\u003e\u003c\/td\u003e\u003ctd style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003eCatalina 10.15, Big Sur 11, Monterey 12, Ventura 13, Sonoma 14\u003c\/td\u003e\u003ctd data-r style=\"text-align:left\"\u003e\u003cstrong\u003eMac Processor\u003c\/strong\u003e\u003c\/td\u003e\u003ctd data-r style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003eIntel or Silicon Architecture\u003c\/td\u003e\u003c\/tr\u003e\n  \u003ctr style=\"background-color:var(--wb-neutral-50);--wb-l:2;--wb-r:6;--wb-lb:transparent;--wb-rb:transparent\"\u003e\u003ctd style=\"text-align:left\"\u003e\u003cstrong\u003eWindows\u003c\/strong\u003e\u003c\/td\u003e\u003ctd style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003eWindows 10 64-bit, Windows 11\u003c\/td\u003e\u003ctd data-r style=\"text-align:left\"\u003e\u003cstrong\u003eWindows Processor\u003c\/strong\u003e\u003c\/td\u003e\u003ctd data-r style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003eX64 compatible Intel or AMD CPU\u003c\/td\u003e\u003c\/tr\u003e\n  \u003ctr style=\"background-color:transparent;--wb-l:3;--wb-r:7;--wb-lb:var(--wb-neutral-50);--wb-rb:var(--wb-neutral-50)\"\u003e\u003ctd style=\"text-align:left\"\u003e\u003cstrong\u003eMemory\u003c\/strong\u003e\u003c\/td\u003e\u003ctd style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003e8 GB\u003c\/td\u003e\u003ctd data-r style=\"text-align:left\"\u003e\u003cstrong\u003eSpectral noise reduction\u003c\/strong\u003e\u003c\/td\u003e\u003ctd data-r style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003eidentification and removal of unwanted sounds\u003c\/td\u003e\u003c\/tr\u003e\n  \u003ctr style=\"background-color:var(--wb-neutral-50);--wb-l:4;--wb-r:8;--wb-lb:transparent;--wb-rb:transparent\"\u003e\u003ctd style=\"text-align:left\"\u003e\u003cstrong\u003eDisk Space\u003c\/strong\u003e\u003c\/td\u003e\u003ctd style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003e16 GB\u003c\/td\u003e\u003ctd data-r style=\"text-align:left\"\u003e\u003cstrong\u003ePAZ Analyzer\u003c\/strong\u003e\u003c\/td\u003e\u003ctd data-r style=\"text-align:left;font-weight:var(--font-body-weight-bolder)\"\u003eaids in spotting artifacts and similar problems\u003c\/td\u003e\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Waves","offers":[{"title":"Default Title","offer_id":54360732238099,"sku":"399487","price":159.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0984\/0872\/6803\/files\/de420d26bdfd52b97ff52006bfc03a336e69012c_WAVES_1178_2779.jpg?v=1789399895","url":"https:\/\/woodbrass.shop\/products\/waves-forensics-package-399487","provider":"Woodbrass.com","version":"1.0","type":"link"}