This paper describes a system for indexing acoustic feature vectors for large-scale speaker search using random projections. Given one or more target feature vectors, large-scale speaker search enables returning similar vectors (in a nearest-neighbors fashion) in sublinear time. The speaker feature space is comprised of i-vectors, derived from Gaussian Mixture Model supervectors. The index and ...
