Fi Ojúkọ̀ Òjú

Free Online Audio Loudness Normalizer

Yan awọn faili rẹ

*Àwọn fáìlì tí a ti parẹ́ lẹ́yìn wákàtí 24

Yi awọn faili to 1 GB pada lọfẹẹ, awọn olumulo Pro le yi awọn faili to 100 GB pada; Forukọsilẹ nisinsinyi

Gbigbe soke

Bii o ṣe le ṣe ìṣàfarawé ìgbà tí a bá kọ́ nínú Audio

1 Fi audio files náà sílẹ̀ tí o fẹ́ láti fi pamọ́ sí ààyè tí o bá jẹ́ ìdájú - àwọn ààyè gbogbo nígbà kan ní àwọn ààyè yìí.

2 Yan àwọn ààyè-iṣẹ́: nipa -14 LUFS fún àwọn ààyè-iṣẹ́ ìṣàfarawé, -16 LUFS fún àwọn àkọ́kọ́, -23 LUFS fún àwọn àkọ́kọ́.

3 Rọ́ọ̀nù ìṣàfihàn; àwọn ìṣàmúlò-ètò àti àwọn ìṣàmúlò-ètò ìṣàfarawé nígbà tí a tí ìṣàmúlò-ètò náà ṣẹ́.

4 Ṣàfikún fáìlì tí a tí ìṣàmúlò-ètò Audio, láti inú àwọn ìṣàmúlò-ètò tí a fi pamọ́ nínú àkọsílẹ̀ kọ̀ǹpútà kọ̀ǹpútà.

Fi Ojúkọ̀ Òjú Awọn ibeere ti a maa n beere nigbagbogbo

Àwọn ìrísí-lẹ́tà ìṣàmúlò-ètò náà ń fá ìṣàfarawé àwọn ìṣàmúlò-ètò?

It does. Ìgúnrégé yìí náà náà nípa ìṣàmúlò-ètò àwọn ààtò àwọn ààtò àwọn ààtò àwọn ààtò àwọn ààtò àwọn ààtò àwọn ààtò àwọn ààtò àwọn ààtò àwọn ààtò àwọn ààtò àwọn ààtò. That determines whether the corrected audio can be written back exactly or has to be re-encoded.

Àkóónú kan fún Audio nibi?

Ya — A tì rí àkóódúrò nínú ìjánu-ìṣàmúlò-ètò náà, láti jẹ́ pé ìjánu-ìjánú tí a kò fi àwọn ààyè àìdájú kò bá iṣẹ́ náà dẹ́kun. Ó wùǹwùn láti mọ́ látigbá tí àwọn àkóónú jẹ́ àtòjọ-ẹ̀yàn tí a gbọ́dọ̀ kọ́ọ̀kan jú fáìlì kan lọ.

Bawo ni Normalize Audio Loudness ṣe fẹ́ ìpelé tó yẹ?

Nípa ìṣàfarawé, Fáìlì náà tí a ṣàyẹwo fún ìṣàmúlò-ètò àti àwọn ìṣàmúlò-ètò ìṣàfarawé, láti inú àwọn ààyè-iṣẹ́ náà nínú àwọn ìṣàmúlò-ètò náà - kò ní ìṣàmúlò-ètò, kò ní ìfàmúlò-ètò, àwọn ìpele nínú. Fáìlì náà nípa ìṣàmúlò-ètò nípa àwọn ìṣàmúlò-ètò tí a tí wa nípa, jú tí a bá lò àwọn ìṣàmúlò-ètò tí a tì fi pamọ́ lọ́wọ́lọ́wọ́.

Kini ìyatọ̀ laarin yìí àti ìṣàfarawé rẹ̀?

Àwọn ìṣàfarawé ìpelè náà ń ló àwọn à

Àwọn àmì-ìwé àti àwọn àwòrán ìṣàfarawé?

Ya - ID3, àwọn àkọ́lé Vorbis àti àtòmù MP4 tí a fi pamọ́ sípapọ̀ nípa àwọn àwòrán tí a fi pamọ́, láti jẹ́ pé àwọn fáìlì tí a tí ìṣàmúlò-ètò náà lóòlù nínú àwọn àkọ́lé.

Àwọn ìrísí-lẹ́tà ìsàlẹ̀-ilà wo ni Normalize Audio Loudness gba?

MP3, WAV, AAC, M4A, FLAC, OGG, Opus, WMA ati AIFF. Kódékì ní pàtó láti inú ìjádé náà, kò ní pàtó ìjádé, láti jẹ́ pé fáìlì tí a kò báà lóòlù nípa fáìlì kan.

Àwọn àwọn ààtò ìwọ̀n fáìlì ní pàtó ní àwọn fáìlì Normalize Audio Loudness?

Ya: free accounts process audio up to 15 MB per file whichever codec you brought; ffmpeg handles the decode and encode. Nínú ìṣàmúlò-ètò náà, àwọn ààyè yìí ní àwọn bítì nínú WAV tí a kò fi pamọ́; fáìlì tí a fi pamọ́ tí o ní ìgbà kan níbẹ̀ kò wa níbì kan.

Ńwò Normalize Audio Loudness náà ń fi ìrànwọ́ audio files mìí?

O dá lórí ìṣàfilọ́lẹ̀. Àwọn ìṣàmúlò-ètò àìdálẹ̀ (WAV, FLAC, AIFF) ní a kọ́ nípa àwọn ààyè àìdálẹ̀

Kini idi ti sáà ìṣàmúlò-ètò ìṣàmúlò-ètò tuntun yẹ́ ki o rọ́ọ̀nù Normalize Audio Loudness?

WEBP.to ti a ṣe ni ayika ti o ti wa ni bayii ti o ti wa ni titun fun gbogbo awọn ti o ti wa ni titun: kan format ti o ṣe lossy, lossless, alpha ati animation, ati ti o ni igbẹkẹle awọn ilẹ ti o kere ju ti JPEG tabi PNG o ti wa ni lati. Awọn eniyan wa nibi ti o ti yan awọn aṣaaju-afẹyinti ti o ti kọja ti o nfa wọn lati gba bandwidth, ati pe ipinnu naa ni kiakia mu awọn miiran: kini iwọn, kini didara, kini o ṣẹlẹ si ifihan. Normalize Audio Loudness wa lori fifi sori ẹrọ kanna ati akọọlẹ kanna, nitorinaa awọn ibeere wọnyi gba idahun ni aaye kan.

Tí a bá tí gbé Normalize Audio Loudness lọ, ohun tí a fẹ́ ṣe nígbà tí a bá tí ṣè?

Àwọn àgbèkalẹ̀ nínú ojú-ìwé yìí tí wọ́ inú àwọn àwòrán láti inú àwọn à Tí o bá ṣè nínú àtòjọ náà ní pataki: yan àwọn píkìsẹ̀lì ní akọkọ àti àwọn ààyè-iṣẹ́ nínú rẹ̀, nitori àwọn ààyè-iṣẹ́ ní àwọn ìṣẹ̀dà tí a bá fẹ́ àti àwọn píkìsẹ̀lì nínú wọn ní owó.

Ńwọn sáà ẹ̀bí tí wọ̀ inú àwọn ààyè-iṣẹ́ náà ló nípa ohunkohun tí wọ̀nyí jẹ́?

The engines are identical — same libraries, same workers, same caps. What is different is the opinion attached, and the opinion here rests on a property of the format this site is named after: àwọn ìṣàmúlò-ètò.webp tí a fẹ́ lè tọju àwọn fèrèsé VP8 tí a gbọ́dọ̀, àwọn tí a kò gbọ́dọ̀, tàbí àwọn ìṣàmúlò-ètò, láti jẹ́ pé àwọn ìṣàmúlò-ètò ìṣàmúlò-ètò tí a fẹ́ nínú fáìlì kan nínú àwọn ìṣàmúlò-ètò kan.