Generally,　phonetic　classification　for　low　rate　speech　coding　is　restricted　to　either　a　simple　binary　voiced/unvoiced　classification　of　entire　speech　frames,　or　alternatively,　a　more　complicated　estimation　of　the　voicing　for　a　set　of　frequency　bands.　A　good　compromise　between　these　two　techniques　is　estimation　of　a　single　cut-off　frequency　that　separates　the　spectrum　into　voiced　(below)　and　unvoiced　(above)　regions.　Many　existing　cut-off　frequency　estimation　methods　use　a　fixed　periodic　spectrum　to　model　voiced　harmonics.　However,　due　to　pitch　jitter,　voiced　harmonics　do　not　always　appear　at　regular　intervals　in　the　spectrum.　In　this　paper　a　voicing　cut-off　estimation　approach　that　combines　speech　energy,　speech　auto-correlation　between　frames　and　residual　harmonic　matching　is　proposed.　Objective　evaluation　indicates　that　the　algorithm　is　accurate　and　reliable.　Subjective　results　obtained　by　embedding　the　algorithm　in　a　low　rate　harmonic　speech　coder　indicate　that　the　technique　is　suitable　for　supporting　high　quality　low　rate　speech　synthesis.　The　proposed　algorithm　also　requires　relatively　low　complexity　and　introduces　only　a　single　frame　of　algorithmic　delay.