16S rRNA next-generation sequencing (NGS) has significantly advanced cervicovaginal microbiome profiling, offering insights into the relationship between vaginal dysbiosis and HPV-associated carcinogenesis. However, reliance on a limited set of 16S hypervariable regions introduces inherent biases that impact results. This study developed standardized workflows for 16S/ITS NGS, with a focus on identifying methodological biases that influence microbial abundance and taxonomic specificity. Commercial NGS tools were employed, including the 16S/ITS QIAseq V1–V9 screening panel, ATCC vaginal microbial standard, and CLC Genomics Workbench integrated with a customized database (VAGIBIOTA) for analysis. The microbial communities of 66 cervical cytology samples were characterized. Among the regions tested, V3V4 exhibited the least quantitative bias, while V1V2 offered the highest specificity. Microbial profiles and Community State Types (CST) (I–V) were broadly consistent with prior studies, with Lactobacillus abundance clustering into three states: L.-dominant (CST I–III, V), L.-diminished (CST IV-A), and L.-depleted (CST IV-B). Differential abundance analysis revealed that anaerobic opportunistic pathogens dominant in CST IV-B (dysbiosis) were also enriched in HSIL and HPV-16 positive samples. Our findings revealed distinct differences in species identification across 16S rRNA hypervariable regions, emphasizing the importance of region selection in clarifying microbial contributions to HPV-associated carcinogenesis.